GTD_GrpFeatures.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Identifying Features Associated with Groups and First Model Attempts\n",
    "\n",
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 170350 entries, 197000000001 to 201701270001\n",
      "Data columns (total 21 columns):\n",
      "iyear             170350 non-null int64\n",
      "country           170350 non-null object\n",
      "success           170350 non-null int64\n",
      "suicide           170350 non-null int64\n",
      "attacktype1       163925 non-null object\n",
      "targtype1         165477 non-null object\n",
      "targsubtype1      161005 non-null object\n",
      "gname             92044 non-null object\n",
      "individual        170350 non-null int64\n",
      "nperps            26173 non-null float64\n",
      "claimed           102742 non-null float64\n",
      "weaptype1         156498 non-null object\n",
      "weapsubtype1      150924 non-null object\n",
      "nkill             160668 non-null float64\n",
      "nwound            155025 non-null float64\n",
      "property          170350 non-null int64\n",
      "propextent        41479 non-null object\n",
      "ishostkid         169903 non-null float64\n",
      "nhostkid          11358 non-null float64\n",
      "ransom            74955 non-null float64\n",
      "hostkidoutcome    6651 non-null object\n",
      "dtypes: float64(7), int64(5), object(9)\n",
      "memory usage: 28.6+ MB\n"
     ]
    }
   ],
   "source": [
    "# Imports\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# columns of interest\n",
    "cols_to_extract = ['eventid', 'iyear',\n",
    " 'country_txt','gname','attacktype1_txt',\n",
    " 'success','suicide',\n",
    " 'weaptype1_txt','weapsubtype1_txt',\n",
    " 'targtype1_txt','targsubtype1_txt',\n",
    " 'individual','nperps','claimed',\n",
    " 'nkill','nwound',\n",
    " 'property','propextent_txt',\n",
    " 'ishostkid','nhostkid','hostkidoutcome_txt','ransom']\n",
    "\n",
    "# Load data\n",
    "df = pd.read_excel('GTD_0617dist/globalterrorismdb_0617dist.xlsx',\n",
    "                   index='eventid',\n",
    "                   usecols=cols_to_extract,\n",
    "                   na_values = ['Unknown','-99','-9','Not Applicable'])\n",
    "\n",
    "# setting index in read statement doesn't seem to work, so do it here\n",
    "df.set_index('eventid',inplace=True) \n",
    "\n",
    "# replace unwanted _txt suffix from column names\n",
    "df.columns = df.columns.str.replace('_txt','')\n",
    "\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract events associated with groups of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total no. events:  170350\n",
      "Number of events affiliated with a group:  91730\n",
      "Number of events affiliated with top 3434 groups: 91730\n",
      "Number of events after excluding groups with less than 10 incidents:  85225\n",
      "Final no. groups:  519\n"
     ]
    }
   ],
   "source": [
    "print('Total no. events: ', len(df))\n",
    "\n",
    "# remove events with no group affiliation\n",
    "no_grp = df.gname.isnull() | df.individual\n",
    "with_grp = ~no_grp\n",
    "print('Number of events affiliated with a group: ',sum(with_grp))\n",
    "df = df[with_grp]\n",
    "\n",
    "# don't need the 'individual' column any more\n",
    "df.drop('individual',axis=1,inplace=True)\n",
    "\n",
    "# only keep the top n groups with the most incidents\n",
    "n_groups = df['gname'].nunique()#50 #for all groups: df['gname'].nunique()\n",
    "top_grps = df['gname'].value_counts().head(n_groups)\n",
    "print('Number of events affiliated with top {} groups: {}'.format(n_groups,sum(top_grps)))\n",
    "\n",
    "# only keep groups with at least 10 incidents\n",
    "top_grps = top_grps[top_grps>10].index\n",
    "\n",
    "# extract events with group of interest\n",
    "df = df[df.gname.isin(top_grps)]\n",
    "print('Number of events after excluding groups with less than 10 incidents: ', len(df))\n",
    "print('Final no. groups: ',df['gname'].nunique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modify some unwanted columns and values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 85225 entries, 197000000002 to 201701270001\n",
      "Data columns (total 20 columns):\n",
      "year              85225 non-null int64\n",
      "country           85225 non-null object\n",
      "success           85225 non-null int64\n",
      "suicide           85225 non-null int64\n",
      "attacktype1       80602 non-null object\n",
      "targtype1         83479 non-null object\n",
      "targsubtype1      81416 non-null object\n",
      "gname             85225 non-null object\n",
      "nperps            14709 non-null float64\n",
      "claimed           85225 non-null float64\n",
      "weaptype1         76148 non-null object\n",
      "weapsubtype1      37993 non-null object\n",
      "nkill             79081 non-null float64\n",
      "nwound            74808 non-null float64\n",
      "property          76903 non-null float64\n",
      "propextent        19925 non-null object\n",
      "ishostkid         84922 non-null float64\n",
      "nhostkid          7126 non-null float64\n",
      "ransom            45336 non-null float64\n",
      "hostkidoutcome    4391 non-null object\n",
      "dtypes: float64(8), int64(3), object(9)\n",
      "memory usage: 13.7+ MB\n"
     ]
    }
   ],
   "source": [
    "# replace some values not correctly dealt with by pandas import\n",
    "df.replace(-9,np.nan,inplace=True)\n",
    "df.replace(-99,np.nan,inplace=True)\n",
    "\n",
    "# rename year column\n",
    "df.rename(columns={'iyear':'year'}, inplace=True)\n",
    "\n",
    "# If no claimed info - treat as not claimed\n",
    "df['claimed'].fillna(0,inplace=True)\n",
    "\n",
    "# remove some values that don't give useful information\n",
    "df['weaptype1'].replace('Other',np.nan,inplace=True)\n",
    "\n",
    "df['weapsubtype1'].replace(['Unknown Gun Type', 'Unknown Explosive Type',\n",
    "                                'Other Explosive Type', 'Unknown Weapon Type',\n",
    "                                'Other Gun Type'], np.nan, inplace=True)\n",
    "\n",
    "df['targtype1'].replace('Other',np.nan,inplace=True)\n",
    "\n",
    "df['targsubtype1'].replace(['Other Personnel', 'Other (including online news agencies)', 'Other Facility'],\n",
    "                               np.nan,inplace=True)\n",
    "\n",
    "\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorise some columns to reduce no. features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th>success</th>\n",
       "      <th>suicide</th>\n",
       "      <th>attacktype1</th>\n",
       "      <th>targtype1</th>\n",
       "      <th>targsubtype1</th>\n",
       "      <th>gname</th>\n",
       "      <th>nperps</th>\n",
       "      <th>claimed</th>\n",
       "      <th>weaptype1</th>\n",
       "      <th>weapsubtype1</th>\n",
       "      <th>nkill</th>\n",
       "      <th>nwound</th>\n",
       "      <th>property</th>\n",
       "      <th>propextent</th>\n",
       "      <th>ishostkid</th>\n",
       "      <th>nhostkid</th>\n",
       "      <th>ransom</th>\n",
       "      <th>hostkidoutcome</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eventid</th>\n",
       "      <th></th>\n",
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       "      <th>197000000002</th>\n",
       "      <td>1970s</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Hostage Taking (Kidnapping)</td>\n",
       "      <td>Government (Diplomatic)</td>\n",
       "      <td>Diplomatic Personnel (outside of embassy, cons...</td>\n",
       "      <td>23rd of September Communist League</td>\n",
       "      <td>2to10</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001010002</th>\n",
       "      <td>1970s</td>\n",
       "      <td>United States</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Armed Assault</td>\n",
       "      <td>Police</td>\n",
       "      <td>Police Building (headquarters, station, school)</td>\n",
       "      <td>Black Nationalists</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>Firearms</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>Minor (likely &lt; $1 million)</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001020001</th>\n",
       "      <td>1970s</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Assassination</td>\n",
       "      <td>Police</td>\n",
       "      <td>Police Security Forces/Officers</td>\n",
       "      <td>Tupamaros (Uruguay)</td>\n",
       "      <td>2to10</td>\n",
       "      <td>no</td>\n",
       "      <td>Firearms</td>\n",
       "      <td>Automatic Weapon</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001050001</th>\n",
       "      <td>1970s</td>\n",
       "      <td>United States</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Bombing/Explosion</td>\n",
       "      <td>Military</td>\n",
       "      <td>Military Barracks/Base/Headquarters/Checkpost</td>\n",
       "      <td>Weather Underground, Weathermen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>Explosives/Bombs/Dynamite</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>Minor (likely &lt; $1 million)</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001060001</th>\n",
       "      <td>1970s</td>\n",
       "      <td>United States</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Facility/Infrastructure Attack</td>\n",
       "      <td>Military</td>\n",
       "      <td>Military Recruiting Station/Academy</td>\n",
       "      <td>Left-Wing Militants</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>Incendiary</td>\n",
       "      <td>Molotov Cocktail/Petrol Bomb</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>Minor (likely &lt; $1 million)</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "               year        country success suicide  \\\n",
       "eventid                                              \n",
       "197000000002  1970s         Mexico     yes      no   \n",
       "197001010002  1970s  United States     yes      no   \n",
       "197001020001  1970s        Uruguay      no      no   \n",
       "197001050001  1970s  United States      no      no   \n",
       "197001060001  1970s  United States     yes      no   \n",
       "\n",
       "                                 attacktype1                targtype1  \\\n",
       "eventid                                                                 \n",
       "197000000002     Hostage Taking (Kidnapping)  Government (Diplomatic)   \n",
       "197001010002                   Armed Assault                   Police   \n",
       "197001020001                   Assassination                   Police   \n",
       "197001050001               Bombing/Explosion                 Military   \n",
       "197001060001  Facility/Infrastructure Attack                 Military   \n",
       "\n",
       "                                                   targsubtype1  \\\n",
       "eventid                                                           \n",
       "197000000002  Diplomatic Personnel (outside of embassy, cons...   \n",
       "197001010002    Police Building (headquarters, station, school)   \n",
       "197001020001                    Police Security Forces/Officers   \n",
       "197001050001      Military Barracks/Base/Headquarters/Checkpost   \n",
       "197001060001                Military Recruiting Station/Academy   \n",
       "\n",
       "                                           gname nperps claimed  \\\n",
       "eventid                                                           \n",
       "197000000002  23rd of September Communist League  2to10      no   \n",
       "197001010002                  Black Nationalists    NaN      no   \n",
       "197001020001                 Tupamaros (Uruguay)  2to10      no   \n",
       "197001050001     Weather Underground, Weathermen    NaN      no   \n",
       "197001060001                 Left-Wing Militants    NaN      no   \n",
       "\n",
       "                              weaptype1                  weapsubtype1 nkill  \\\n",
       "eventid                                                                       \n",
       "197000000002                        NaN                           NaN     0   \n",
       "197001010002                   Firearms                           NaN     0   \n",
       "197001020001                   Firearms              Automatic Weapon     0   \n",
       "197001050001  Explosives/Bombs/Dynamite                           NaN     0   \n",
       "197001060001                 Incendiary  Molotov Cocktail/Petrol Bomb     0   \n",
       "\n",
       "             nwound property                   propextent ishostkid nhostkid  \\\n",
       "eventid                                                                        \n",
       "197000000002      0       no                          NaN       yes        1   \n",
       "197001010002      0      yes  Minor (likely < $1 million)        no      NaN   \n",
       "197001020001      0       no                          NaN        no      NaN   \n",
       "197001050001      0       no  Minor (likely < $1 million)        no      NaN   \n",
       "197001060001      0      yes  Minor (likely < $1 million)        no      NaN   \n",
       "\n",
       "             ransom hostkidoutcome  \n",
       "eventid                             \n",
       "197000000002    yes            NaN  \n",
       "197001010002     no            NaN  \n",
       "197001020001     no            NaN  \n",
       "197001050001     no            NaN  \n",
       "197001060001     no            NaN  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Numeric columns - convert to values for 0, 1, 2-10, and more than 10 \n",
    "conv_numeric = ['nkill','nwound','nperps','nhostkid']\n",
    "\n",
    "for col in conv_numeric:\n",
    "    df[col] = pd.cut(df[col],\n",
    "                        [-0.1,0.9,1.9,10.9,max(df[col])+0.1],\n",
    "                        labels=['0','1','2to10','11+'])\n",
    "\n",
    "# boolean columns - convert to yes/no to help identification in dummy variables later\n",
    "conv_bool = ['success','suicide','claimed','property','ishostkid','ransom']\n",
    "\n",
    "for col in conv_bool:\n",
    "    df[col].replace({0:'no',1:'yes'},inplace=True)\n",
    "\n",
    "# bin year in to decades\n",
    "df['year'] = pd.cut(df['year'],\n",
    "                        [1969.9,1979.9,1989.9,1999.9,2009.9,2019.9],\n",
    "                        labels=['1970s','1980s','1990s','2000s','2010s'])  \n",
    "\n",
    "display(df.head())\n",
    "\n",
    "# warning message below r.e. empty bins"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create training and testing datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "eventid\n",
       "197000000002    23rd of September Communist League\n",
       "197001010002                    Black Nationalists\n",
       "197001020001                   Tupamaros (Uruguay)\n",
       "197001050001       Weather Underground, Weathermen\n",
       "197001060001                   Left-Wing Militants\n",
       "Name: gname, dtype: object"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th>success</th>\n",
       "      <th>suicide</th>\n",
       "      <th>attacktype1</th>\n",
       "      <th>targtype1</th>\n",
       "      <th>targsubtype1</th>\n",
       "      <th>nperps</th>\n",
       "      <th>claimed</th>\n",
       "      <th>weaptype1</th>\n",
       "      <th>weapsubtype1</th>\n",
       "      <th>nkill</th>\n",
       "      <th>nwound</th>\n",
       "      <th>property</th>\n",
       "      <th>propextent</th>\n",
       "      <th>ishostkid</th>\n",
       "      <th>nhostkid</th>\n",
       "      <th>ransom</th>\n",
       "      <th>hostkidoutcome</th>\n",
       "    </tr>\n",
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       "      <th>eventid</th>\n",
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       "      <th>197000000002</th>\n",
       "      <td>1970s</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Hostage Taking (Kidnapping)</td>\n",
       "      <td>Government (Diplomatic)</td>\n",
       "      <td>Diplomatic Personnel (outside of embassy, cons...</td>\n",
       "      <td>2to10</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yes</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001010002</th>\n",
       "      <td>1970s</td>\n",
       "      <td>United States</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Armed Assault</td>\n",
       "      <td>Police</td>\n",
       "      <td>Police Building (headquarters, station, school)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>Firearms</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>Minor (likely &lt; $1 million)</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001020001</th>\n",
       "      <td>1970s</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Assassination</td>\n",
       "      <td>Police</td>\n",
       "      <td>Police Security Forces/Officers</td>\n",
       "      <td>2to10</td>\n",
       "      <td>no</td>\n",
       "      <td>Firearms</td>\n",
       "      <td>Automatic Weapon</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001050001</th>\n",
       "      <td>1970s</td>\n",
       "      <td>United States</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Bombing/Explosion</td>\n",
       "      <td>Military</td>\n",
       "      <td>Military Barracks/Base/Headquarters/Checkpost</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>Explosives/Bombs/Dynamite</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>Minor (likely &lt; $1 million)</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197001060001</th>\n",
       "      <td>1970s</td>\n",
       "      <td>United States</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>Facility/Infrastructure Attack</td>\n",
       "      <td>Military</td>\n",
       "      <td>Military Recruiting Station/Academy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>Incendiary</td>\n",
       "      <td>Molotov Cocktail/Petrol Bomb</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>Minor (likely &lt; $1 million)</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               year        country success suicide  \\\n",
       "eventid                                              \n",
       "197000000002  1970s         Mexico     yes      no   \n",
       "197001010002  1970s  United States     yes      no   \n",
       "197001020001  1970s        Uruguay      no      no   \n",
       "197001050001  1970s  United States      no      no   \n",
       "197001060001  1970s  United States     yes      no   \n",
       "\n",
       "                                 attacktype1                targtype1  \\\n",
       "eventid                                                                 \n",
       "197000000002     Hostage Taking (Kidnapping)  Government (Diplomatic)   \n",
       "197001010002                   Armed Assault                   Police   \n",
       "197001020001                   Assassination                   Police   \n",
       "197001050001               Bombing/Explosion                 Military   \n",
       "197001060001  Facility/Infrastructure Attack                 Military   \n",
       "\n",
       "                                                   targsubtype1 nperps  \\\n",
       "eventid                                                                  \n",
       "197000000002  Diplomatic Personnel (outside of embassy, cons...  2to10   \n",
       "197001010002    Police Building (headquarters, station, school)    NaN   \n",
       "197001020001                    Police Security Forces/Officers  2to10   \n",
       "197001050001      Military Barracks/Base/Headquarters/Checkpost    NaN   \n",
       "197001060001                Military Recruiting Station/Academy    NaN   \n",
       "\n",
       "             claimed                  weaptype1                  weapsubtype1  \\\n",
       "eventid                                                                         \n",
       "197000000002      no                        NaN                           NaN   \n",
       "197001010002      no                   Firearms                           NaN   \n",
       "197001020001      no                   Firearms              Automatic Weapon   \n",
       "197001050001      no  Explosives/Bombs/Dynamite                           NaN   \n",
       "197001060001      no                 Incendiary  Molotov Cocktail/Petrol Bomb   \n",
       "\n",
       "             nkill nwound property                   propextent ishostkid  \\\n",
       "eventid                                                                     \n",
       "197000000002     0      0       no                          NaN       yes   \n",
       "197001010002     0      0      yes  Minor (likely < $1 million)        no   \n",
       "197001020001     0      0       no                          NaN        no   \n",
       "197001050001     0      0       no  Minor (likely < $1 million)        no   \n",
       "197001060001     0      0      yes  Minor (likely < $1 million)        no   \n",
       "\n",
       "             nhostkid ransom hostkidoutcome  \n",
       "eventid                                      \n",
       "197000000002        1    yes            NaN  \n",
       "197001010002      NaN     no            NaN  \n",
       "197001020001      NaN     no            NaN  \n",
       "197001050001      NaN     no            NaN  \n",
       "197001060001      NaN     no            NaN  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: X shape = (59657, 19) , Y shape= (59657,)\n",
      "Test: X shape = (25568, 19) , Y shape= (25568,)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# labels\n",
    "y = df['gname']\n",
    "display(y.head())\n",
    "\n",
    "# features\n",
    "X = df.drop('gname',axis=1)\n",
    "display(X.head())\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y,test_size=0.3, random_state=42)\n",
    "print('Train: X shape =',X_train.shape,', Y shape=',y_train.shape)\n",
    "print('Test: X shape =',X_test.shape,', Y shape=',y_test.shape)\n",
    "\n",
    "# make some combined data frames with both labels and features. Useful later.\n",
    "df_train = X_train.copy()\n",
    "df_train['gname'] =  y_train\n",
    "\n",
    "df_test = X_test.copy()\n",
    "df_test['gname'] = y_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Dummy variables for Each Category Value\n",
    "\n",
    "Gives a bool column for each unique value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>16 January Organization for the Liberation of Tripoli</th>\n",
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       "      <th>Abu Nidal Organization (ANO)</th>\n",
       "      <th>Abu Sayyaf Group (ASG)</th>\n",
       "      <th>...</th>\n",
       "      <th>Weather Underground, Weathermen</th>\n",
       "      <th>White Wolves</th>\n",
       "      <th>White extremists</th>\n",
       "      <th>Workers' Self-Defense Movement (MAO)</th>\n",
       "      <th>Young Communist League</th>\n",
       "      <th>Youths</th>\n",
       "      <th>Zapatista National Liberation Army</th>\n",
       "      <th>Zebra killers</th>\n",
       "      <th>Zimbabwe African Nationalist Union (ZANU)</th>\n",
       "      <th>Zimbabwe African People's Union</th>\n",
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       "      <td>0</td>\n",
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       "<p>5 rows × 519 columns</p>\n",
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      "text/plain": [
       "              16 January Organization for the Liberation of Tripoli  \\\n",
       "eventid                                                               \n",
       "201611290005                                                  0       \n",
       "199210300002                                                  0       \n",
       "198902070002                                                  0       \n",
       "199907190002                                                  0       \n",
       "200711190003                                                  0       \n",
       "\n",
       "              20 December Movement (M-20)  23rd of September Communist League  \\\n",
       "eventid                                                                         \n",
       "201611290005                            0                                   0   \n",
       "199210300002                            0                                   0   \n",
       "198902070002                            0                                   0   \n",
       "199907190002                            0                                   0   \n",
       "200711190003                            0                                   0   \n",
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       "              2nd of June Movement  31 January People's Front (FP-31)  \\\n",
       "eventid                                                                 \n",
       "201611290005                     0                                  0   \n",
       "199210300002                     0                                  0   \n",
       "198902070002                     0                                  0   \n",
       "199907190002                     0                                  0   \n",
       "200711190003                     0                                  0   \n",
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       "              9 February  Abdullah Azzam Brigades  Abu Hafs al-Masri Brigades  \\\n",
       "eventid                                                                         \n",
       "201611290005           0                        0                           0   \n",
       "199210300002           0                        0                           0   \n",
       "198902070002           0                        0                           0   \n",
       "199907190002           0                        0                           0   \n",
       "200711190003           0                        0                           0   \n",
       "\n",
       "              Abu Nidal Organization (ANO)  Abu Sayyaf Group (ASG)  \\\n",
       "eventid                                                              \n",
       "201611290005                             0                       0   \n",
       "199210300002                             0                       0   \n",
       "198902070002                             0                       0   \n",
       "199907190002                             0                       0   \n",
       "200711190003                             0                       0   \n",
       "\n",
       "                           ...                 \\\n",
       "eventid                    ...                  \n",
       "201611290005               ...                  \n",
       "199210300002               ...                  \n",
       "198902070002               ...                  \n",
       "199907190002               ...                  \n",
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       "\n",
       "              Weather Underground, Weathermen  White Wolves  White extremists  \\\n",
       "eventid                                                                         \n",
       "201611290005                                0             0                 0   \n",
       "199210300002                                0             0                 0   \n",
       "198902070002                                0             0                 0   \n",
       "199907190002                                0             0                 0   \n",
       "200711190003                                0             0                 0   \n",
       "\n",
       "              Workers' Self-Defense Movement (MAO)  Young Communist League  \\\n",
       "eventid                                                                      \n",
       "201611290005                                     0                       0   \n",
       "199210300002                                     0                       0   \n",
       "198902070002                                     0                       0   \n",
       "199907190002                                     0                       0   \n",
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       "\n",
       "              Youths  Zapatista National Liberation Army  Zebra killers  \\\n",
       "eventid                                                                   \n",
       "201611290005       0                                   0              0   \n",
       "199210300002       0                                   0              0   \n",
       "198902070002       0                                   0              0   \n",
       "199907190002       0                                   0              0   \n",
       "200711190003       0                                   0              0   \n",
       "\n",
       "              Zimbabwe African Nationalist Union (ZANU)  \\\n",
       "eventid                                                   \n",
       "201611290005                                          0   \n",
       "199210300002                                          0   \n",
       "198902070002                                          0   \n",
       "199907190002                                          0   \n",
       "200711190003                                          0   \n",
       "\n",
       "              Zimbabwe African People's Union  \n",
       "eventid                                        \n",
       "201611290005                                0  \n",
       "199210300002                                0  \n",
       "198902070002                                0  \n",
       "199907190002                                0  \n",
       "200711190003                                0  \n",
       "\n",
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     "output_type": "display_data"
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>199210300002</th>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>198902070002</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199907190002</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>200711190003</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 367 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              year_1970s  year_1980s  year_1990s  year_2000s  year_2010s  \\\n",
       "eventid                                                                    \n",
       "201611290005           0           0           0           0           1   \n",
       "199210300002           0           0           1           0           0   \n",
       "198902070002           0           1           0           0           0   \n",
       "199907190002           0           0           1           0           0   \n",
       "200711190003           0           0           0           1           0   \n",
       "\n",
       "              country_Afghanistan  country_Algeria  country_Andorra  \\\n",
       "eventid                                                               \n",
       "201611290005                    0                0                0   \n",
       "199210300002                    0                0                0   \n",
       "198902070002                    0                0                0   \n",
       "199907190002                    0                0                0   \n",
       "200711190003                    1                0                0   \n",
       "\n",
       "              country_Angola  country_Argentina  \\\n",
       "eventid                                           \n",
       "201611290005               0                  0   \n",
       "199210300002               1                  0   \n",
       "198902070002               0                  0   \n",
       "199907190002               0                  0   \n",
       "200711190003               0                  0   \n",
       "\n",
       "                            ...                 nhostkid_2to10  nhostkid_11+  \\\n",
       "eventid                     ...                                                \n",
       "201611290005                ...                              0             0   \n",
       "199210300002                ...                              0             0   \n",
       "198902070002                ...                              0             0   \n",
       "199907190002                ...                              0             0   \n",
       "200711190003                ...                              0             0   \n",
       "\n",
       "              ransom_no  ransom_yes  hostkidoutcome_Attempted Rescue  \\\n",
       "eventid                                                                \n",
       "201611290005          0           0                                0   \n",
       "199210300002          1           0                                0   \n",
       "198902070002          1           0                                0   \n",
       "199907190002          0           0                                0   \n",
       "200711190003          0           0                                0   \n",
       "\n",
       "              hostkidoutcome_Combination  \\\n",
       "eventid                                    \n",
       "201611290005                           0   \n",
       "199210300002                           0   \n",
       "198902070002                           0   \n",
       "199907190002                           0   \n",
       "200711190003                           0   \n",
       "\n",
       "              hostkidoutcome_Hostage(s) escaped (not during rescue attempt)  \\\n",
       "eventid                                                                       \n",
       "201611290005                                                  0               \n",
       "199210300002                                                  0               \n",
       "198902070002                                                  0               \n",
       "199907190002                                                  0               \n",
       "200711190003                                                  0               \n",
       "\n",
       "              hostkidoutcome_Hostage(s) killed (not during rescue attempt)  \\\n",
       "eventid                                                                      \n",
       "201611290005                                                  0              \n",
       "199210300002                                                  0              \n",
       "198902070002                                                  0              \n",
       "199907190002                                                  0              \n",
       "200711190003                                                  0              \n",
       "\n",
       "              hostkidoutcome_Hostage(s) released by perpetrators  \\\n",
       "eventid                                                            \n",
       "201611290005                                                  0    \n",
       "199210300002                                                  0    \n",
       "198902070002                                                  0    \n",
       "199907190002                                                  0    \n",
       "200711190003                                                  0    \n",
       "\n",
       "              hostkidoutcome_Successful Rescue  \n",
       "eventid                                         \n",
       "201611290005                                 0  \n",
       "199210300002                                 0  \n",
       "198902070002                                 0  \n",
       "199907190002                                 0  \n",
       "200711190003                                 0  \n",
       "\n",
       "[5 rows x 367 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# labels\n",
    "# do on full dataset first to make sure same columns in test and train\n",
    "y_dum = pd.get_dummies(y)\n",
    "y_dum_train = y_dum.loc[y_train.index]\n",
    "y_dum_test = y_dum.loc[y_test.index]\n",
    "\n",
    "display(y_dum_train.head())\n",
    "\n",
    "# features\n",
    "# do on full dataset first to make sure same columns in test and train\n",
    "X_dum = pd.get_dummies(X)\n",
    "X_dum_train = X_dum.loc[X_train.index]\n",
    "X_dum_test = X_dum.loc[X_test.index]\n",
    "\n",
    "# NaN values in test data can destroy predictions so remove them\n",
    "X_dum_test.fillna(0,inplace=True) \n",
    "\n",
    "display(X_dum_train.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Characterising Values for each Group\n",
    "i.e. the feature values that are most characteristic of an attack by each group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: No instances of country_Andorra\n",
      "Warning: No instances of country_Bhutan\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\jackr\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:20: RuntimeWarning: divide by zero encountered in longlong_scalars\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: No instances of country_Cuba\n",
      "Warning: No instances of country_Hungary\n",
      "Warning: No instances of country_New Zealand\n",
      "Warning: No instances of country_Poland\n",
      "Warning: No instances of country_Republic of the Congo\n",
      "Warning: No instances of country_Trinidad and Tobago\n",
      "Warning: No instances of weaptype1_Biological\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 519 entries, Taliban to Orange Volunteers (OV)\n",
      "Columns: 367 entries, year_1970s to hostkidoutcome_Successful Rescue\n",
      "dtypes: float64(367)\n",
      "memory usage: 1.5+ MB\n"
     ]
    }
   ],
   "source": [
    "# no. incidents associated with each group\n",
    "grp_incs = y.value_counts()\n",
    "\n",
    "# add group name column to the data frame of dummies\n",
    "df_dum_train = X_dum_train.copy()\n",
    "df_dum_train['gname'] =  y_train\n",
    "\n",
    "# loop over all columns excluding gname\n",
    "col_tfidf = dict()\n",
    "\n",
    "for col in df_dum_train.drop('gname',axis=1).columns:\n",
    "    # for each group, how many times this unique value appears\n",
    "    grp_cnts = df_dum_train.groupby('gname')[col].sum()\n",
    "    \n",
    "    # count how many groups have an incident including this unique value\n",
    "    # convert this for tf-idf weight using log(n_groups/count)\n",
    "    if (grp_cnts>0).sum()==0:\n",
    "        print('Warning: No instances of',col)\n",
    "        \n",
    "    w_col = np.log(n_groups/((grp_cnts>0).sum()))\n",
    "    \n",
    "    # multiply w_col by no. occurences each column value to get weight for each group\n",
    "    col_tfidf[col] = (grp_cnts*w_col)\n",
    "    \n",
    "# merge unique values for each column in to one large data frame\n",
    "w_tfidf = pd.DataFrame(col_tfidf,\n",
    "                       index=top_grps,\n",
    "                       columns=df_dum_train.drop('gname',axis=1).columns) #ensures columns in same order\n",
    "\n",
    "# get rid of NaN weights\n",
    "w_tfidf.fillna(0,inplace=True)\n",
    "\n",
    "w_tfidf.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Print Top n Features for Top m Groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "country_Afghanistan    23727.047569\n",
      "year_2010s             10172.579676\n",
      "suicide_no              7953.230259\n",
      "success_yes             7936.758333\n",
      "ishostkid_no            7793.003893\n",
      "Name: Taliban, dtype: float64\n",
      "----------------------------------------------\n",
      "country_Peru    16598.756445\n",
      "ransom_no        6298.127511\n",
      "year_1980s       6152.028534\n",
      "claimed_no       6117.600064\n",
      "suicide_no       5993.738746\n",
      "Name: Shining Path (SL), dtype: float64\n",
      "----------------------------------------------\n",
      "country_Iraq    12904.910749\n",
      "year_2010s       8035.305061\n",
      "success_yes      5061.669519\n",
      "ishostkid_no     5052.211990\n",
      "suicide_no       4391.377316\n",
      "Name: Islamic State of Iraq and the Levant (ISIL), dtype: float64\n",
      "----------------------------------------------\n",
      "country_El Salvador    11943.282890\n",
      "year_1980s              5006.646461\n",
      "ransom_no               4683.893106\n",
      "claimed_no              4507.501848\n",
      "suicide_no              4406.493933\n",
      "Name: Farabundo Marti National Liberation Front (FMLN), dtype: float64\n",
      "----------------------------------------------\n",
      "country_Somalia    9141.024217\n",
      "year_2010s         4780.397375\n",
      "suicide_no         3342.661993\n",
      "success_yes        3255.281480\n",
      "ishostkid_no       3111.527040\n",
      "Name: Al-Shabaab, dtype: float64\n",
      "----------------------------------------------\n",
      "country_United Kingdom    7998.392970\n",
      "ransom_no                 3747.114485\n",
      "claimed_no                3657.029801\n",
      "suicide_no                3586.417446\n",
      "ishostkid_no              3501.177234\n",
      "Name: Irish Republican Army (IRA), dtype: float64\n",
      "----------------------------------------------\n",
      "country_Colombia    7730.303727\n",
      "claimed_no          3227.927996\n",
      "suicide_no          3227.397786\n",
      "success_yes         2958.315070\n",
      "ishostkid_no        2727.551362\n",
      "Name: Revolutionary Armed Forces of Colombia (FARC), dtype: float64\n",
      "----------------------------------------------\n",
      "country_Philippines    8120.105909\n",
      "suicide_no             3238.735249\n",
      "claimed_no             2949.591689\n",
      "success_yes            2935.617000\n",
      "ishostkid_no           2894.003873\n",
      "Name: New People's Army (NPA), dtype: float64\n",
      "----------------------------------------------\n",
      "country_Turkey    6345.033774\n",
      "suicide_no        2783.347154\n",
      "claimed_no        2738.906569\n",
      "success_yes       2657.565648\n",
      "ishostkid_no      2615.952520\n",
      "Name: Kurdistan Workers' Party (PKK), dtype: float64\n",
      "----------------------------------------------\n",
      "country_Nigeria    6605.895479\n",
      "year_2010s         3803.130543\n",
      "success_yes        2557.315841\n",
      "claimed_no         2485.697846\n",
      "ishostkid_no       2481.655609\n",
      "Name: Boko Haram, dtype: float64\n",
      "----------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "n_print_grp=10\n",
    "n_print_feat=5\n",
    "\n",
    "for grp in grp_incs.head(n_print_grp).index:    \n",
    "    print(w_tfidf.loc[grp].sort_values(ascending=False).head(n_print_feat))\n",
    "    print('----------------------------------------------')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Using tf-idf Type Weights Derived Above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overall accuracy 0.245697747184\n",
      "precision 0.245697747184\n",
      "recall 0.245697747184\n",
      "accuracy 0.245697747184\n",
      "confusion matrix (top 20 grps):\n"
     ]
    },
    {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>361</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>271</td>\n",
       "      <td>353</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>144</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>367</td>\n",
       "      <td>263</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>308</td>\n",
       "      <td>334</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>555</td>\n",
       "      <td>4</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>49</td>\n",
       "      <td>565</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>431</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>145</td>\n",
       "      <td>311</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>65</td>\n",
       "      <td>329</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>361</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>309</td>\n",
       "      <td>41</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3</td>\n",
       "      <td>338</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>273</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>269</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0     1     2     3    4    5    6   7   8   9   10  11  12  13  14  15  \\\n",
       "0   1929     2     0     0    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "1      2  1377     0     0    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "2    156     2  1095     0    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "3      0    10     0  1009    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "4    582     3    13     0  216    0    0   0   0   0   0   0   0   0   0   0   \n",
       "5      2   408     0     0    0  361    0   0   0   0   0   0   0   0   0   0   \n",
       "6    271   353     1     2    0    0  144   0   0   0   0   0   0   0   0   0   \n",
       "7    367   263     0     0    0    0    0  70   0   0   0   0   0   0   0   0   \n",
       "8    308   334     7     0    0    0    0   0  15   0   0   0   0   0   0   0   \n",
       "9    555     4    59     0    0    0    0   0   0  15   0   0   0   0   0   0   \n",
       "10    49   565     0     0    0    0    0   0   0   0  24   0   0   0   0   0   \n",
       "11   431    76     0     0    0    0    0   0   0   0   0   7   0   0   0   0   \n",
       "12   145   311    17     0    0    0    0   0   0   0   0   0  17   0   0   0   \n",
       "13    65   329     0     1    0    0   56   0   0   0   0   0   0   0   0   0   \n",
       "14   361    35     0     0    0    0    0   0   0   0   0   0   0   0   1   0   \n",
       "15   309    41    28     0    0    0    0   0   0   0   0   0   0   0   0   1   \n",
       "16     3   338     0     0    0    1    0   0   0   0   0   0   0   0   0   0   \n",
       "17   273     0    29     0    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "18     0   238     0     4    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "19   269     2    10     0    0    0    0   0   0   0   0   0   0   0   0   0   \n",
       "\n",
       "    16  17  18  19  \n",
       "0    0   0   0   0  \n",
       "1    0   0   0   0  \n",
       "2    0   0   0   0  \n",
       "3    0   0   0   0  \n",
       "4    0   0   0   0  \n",
       "5    0   0   0   0  \n",
       "6    0   0   0   0  \n",
       "7    0   0   0   0  \n",
       "8    0   0   0   0  \n",
       "9    0   0   0   0  \n",
       "10   0   0   0   0  \n",
       "11   0   0   0   0  \n",
       "12   0   0   0   0  \n",
       "13   0   0   0   0  \n",
       "14   0   0   0   0  \n",
       "15   0   0   0   0  \n",
       "16   0   0   0   0  \n",
       "17   0   1   0   0  \n",
       "18   0   0   0   0  \n",
       "19   0   0   0   0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "grp13:  National Liberation Army of Colombia (ELN)\n",
      "grp6:  Revolutionary Armed Forces of Colombia (FARC)\n",
      "----------------------------\n",
      "grp14:  Maoists\n",
      "grp11:  Communist Party of India - Maoist (CPI-Maoist)\n",
      "----------------------------\n",
      "grp19:  Houthi extremists (Ansar Allah)\n",
      "grp17:  Al-Qaida in the Arabian Peninsula (AQAP)\n",
      "----------------------------\n"
     ]
    }
   ],
   "source": [
    "# subtract neg_scale*weight for features not present in event\n",
    "# but present in group\n",
    "neg_scale = 0.25 \n",
    "\n",
    "# matrix multiply test events by group weights for each feature\n",
    "tfidf_events = pd.DataFrame(np.inner(X_dum_test,w_tfidf),index=X_dum_test.index,columns=w_tfidf.index)\n",
    "\n",
    "# subtract contribution of negative cases\n",
    "tfidf_events = tfidf_events - neg_scale*pd.DataFrame(np.inner(X_dum_test.replace({0:1,1:0}),w_tfidf),index=X_dum_test.index,columns=w_tfidf.index)\n",
    "\n",
    "tfidf_pred = pd.DataFrame({'gname':y_test,'pred':tfidf_events.idxmax(axis=1)})\n",
    "tfidf_pred['true'] = tfidf_pred.gname == tfidf_pred.pred\n",
    "\n",
    "# stats on accuracy of model overall and per group\n",
    "print('overall accuracy',sum(tfidf_pred.true)/len(tfidf_pred))\n",
    "\n",
    "# calculate metrics\n",
    "from sklearn.metrics import precision_score, recall_score, accuracy_score, confusion_matrix\n",
    "\n",
    "print('precision',precision_score(tfidf_pred.gname, tfidf_pred.pred, labels=top_grps,average='micro'))\n",
    "print('recall',recall_score(tfidf_pred.gname, tfidf_pred.pred, labels=top_grps,average='micro'))\n",
    "print('accuracy',accuracy_score(tfidf_pred.gname, tfidf_pred.pred))\n",
    "print('confusion matrix (top 20 grps):')\n",
    "cmatrix = confusion_matrix(tfidf_pred.gname, tfidf_pred.pred,labels=top_grps)        \n",
    "display(pd.DataFrame(cmatrix).iloc[:20,:20])\n",
    "\n",
    "print('grp13: ',top_grps[13])\n",
    "print('grp6: ',top_grps[6])\n",
    "print('----------------------------')\n",
    "print('grp14: ',top_grps[14])\n",
    "print('grp11: ',top_grps[11])\n",
    "print('----------------------------')\n",
    "print('grp19: ',top_grps[19])\n",
    "print('grp17: ',top_grps[17])\n",
    "print('----------------------------')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================\n",
      "Frequent groups with incorrect predictions\n",
      "==========================\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Kurdistan Workers' Party (PKK)                    649\n",
       "New People's Army (NPA)                           630\n",
       "Revolutionary Armed Forces of Colombia (FARC)     627\n",
       "Boko Haram                                        618\n",
       "Basque Fatherland and Freedom (ETA)               614\n",
       "Al-Shabaab                                        598\n",
       "Communist Party of India - Maoist (CPI-Maoist)    507\n",
       "Liberation Tigers of Tamil Eelam (LTTE)           473\n",
       "National Liberation Army of Colombia (ELN)        451\n",
       "Irish Republican Army (IRA)                       410\n",
       "Name: gname, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================\n",
      "Incorrect predictions\n",
      "==========================\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Shining Path (SL)                                   9690\n",
       "Taliban                                             8300\n",
       "Islamic State of Iraq and the Levant (ISIL)          610\n",
       "Irish Republican Army (IRA)                          307\n",
       "Farabundo Marti National Liberation Front (FMLN)     171\n",
       "Revolutionary Armed Forces of Colombia (FARC)         95\n",
       "New People's Army (NPA)                               73\n",
       "Communist Party of India - Maoist (CPI-Maoist)        16\n",
       "Basque Fatherland and Freedom (ETA)                    9\n",
       "Al-Shabaab                                             7\n",
       "Name: pred, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('==========================')\n",
    "print('Frequent groups with incorrect predictions')\n",
    "print('==========================')\n",
    "display(tfidf_pred[(~tfidf_pred.true)].gname.value_counts().head(10))\n",
    "\n",
    "print('==========================')\n",
    "print('Incorrect predictions')\n",
    "print('==========================')\n",
    "display(tfidf_pred[(~tfidf_pred.true)].pred.value_counts().head(10))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit a Classifier to the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy score: 0.627816020025\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\jackr\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\ranking.py:444: RuntimeWarning: invalid value encountered in true_divide\n",
      "  recall = tps / tps[-1]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision score: nan\n"
     ]
    }
   ],
   "source": [
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.svm import LinearSVC\n",
    "from sklearn.metrics import average_precision_score, accuracy_score\n",
    "\n",
    "model=OneVsRestClassifier(LinearSVC(random_state=0)).fit(X_dum_train.fillna(0), y_dum_train.fillna(0))\n",
    "\n",
    "y_svc_pred = model.predict(X_dum_test.fillna(0))\n",
    "\n",
    "print('Accuracy score:',accuracy_score(y_dum_test,y_svc_pred))\n",
    "print('Precision score:',average_precision_score(y_dum_test,y_svc_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Investigate the Results of the Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Groups commonly labelled incorrectly:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Revolutionary Armed Forces of Colombia (FARC)     348\n",
       "National Liberation Army of Colombia (ELN)        345\n",
       "Maoists                                           244\n",
       "Communist Party of India - Maoist (CPI-Maoist)    219\n",
       "Al-Qaida in Iraq                                  176\n",
       "Name: true, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "United Popular Action Front (FAPU)   NaN\n",
       "Weather Underground, Weathermen      NaN\n",
       "White Wolves                         NaN\n",
       "Youths                               NaN\n",
       "Zimbabwe African People's Union      NaN\n",
       "Name: true, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Common incorrect predictions:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "16 January Organization for the Liberation of Tripoli    5552\n",
       "Islamic State of Iraq and the Levant (ISIL)               215\n",
       "Revolutionary Armed Forces of Colombia (FARC)             162\n",
       "Communist Party of India - Maoist (CPI-Maoist)            162\n",
       "Shining Path (SL)                                         161\n",
       "Name: pred, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Sunni Muslim extremists                                  NaN\n",
       "Supreme Council for Islamic Revolution in Iraq (SCIRI)   NaN\n",
       "Tripura National Volunteers (TNV)                        NaN\n",
       "United Democratic Liberation Army (UDLA)                 NaN\n",
       "Zimbabwe African People's Union                          NaN\n",
       "Name: pred, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Groups commonly labelled correctly:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Taliban                                             1907\n",
       "Shining Path (SL)                                   1363\n",
       "Islamic State of Iraq and the Levant (ISIL)         1111\n",
       "Farabundo Marti National Liberation Front (FMLN)     995\n",
       "Al-Shabaab                                           803\n",
       "Name: true, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "16 January Organization for the Liberation of Tripoli    1.0\n",
       "Paraguayan People's Army (EPP)                           1.0\n",
       "Maximiliano Gomez Revolutionary Brigade                  1.0\n",
       "Tupamaros (Uruguay)                                      1.0\n",
       "Tupac Katari Guerrilla Army (EGTK)                       1.0\n",
       "Name: true, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Common correct predictions:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Taliban                                             1907\n",
       "Shining Path (SL)                                   1363\n",
       "Islamic State of Iraq and the Levant (ISIL)         1111\n",
       "Farabundo Marti National Liberation Front (FMLN)     995\n",
       "Al-Shabaab                                           803\n",
       "Name: pred, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Brunswijk Jungle Commando    1.0\n",
       "Sandinistas                  1.0\n",
       "Forqan Group                 1.0\n",
       "Dishmish Regiment            1.0\n",
       "Alfaro Vive                  1.0\n",
       "Name: pred, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# extract group for each event in test data\n",
    "#y_test = y_test.stack()\n",
    "#y_test = y_test[y_test>0].index.get_level_values(1)\n",
    "\n",
    "# extract prediction for each event in test data\n",
    "labels_svc_pred = y_dum_test.columns[y_svc_pred.argmax(axis=1)]\n",
    "\n",
    "# create a data frame of labels and predictions\n",
    "labels_svc = pd.DataFrame({'true':y_test.values, 'pred':labels_svc_pred.values})\n",
    "\n",
    "# was the predcition correct?\n",
    "labels_svc['correct'] = labels_svc['pred']==labels_svc['true']\n",
    "\n",
    "# labelled correctly / total events\n",
    "frac_true_svc = (labels_svc.loc[labels_svc.correct,'true'].value_counts()/labels_svc['true'].value_counts()).sort_values(ascending=False)\n",
    "\n",
    "# predicted correctly / predicted total\n",
    "frac_pred_svc = (labels_svc.loc[labels_svc.correct,'pred'].value_counts()/labels_svc['pred'].value_counts()).sort_values(ascending=False)\n",
    "\n",
    "\n",
    "print('-------------------------------------------')\n",
    "print('Groups commonly labelled incorrectly:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_svc.loc[~labels_svc.correct,'true'].value_counts().head(5))\n",
    "display(frac_true_svc.tail(5).sort_values())\n",
    "print('-------------------------------------------')\n",
    "print('Common incorrect predictions:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_svc.loc[~labels_svc.correct,'pred'].value_counts().head(5))\n",
    "display(frac_pred_svc.tail(5).sort_values())\n",
    "print('-------------------------------------------')\n",
    "print('Groups commonly labelled correctly:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_svc.loc[labels_svc.correct,'true'].value_counts().head(5))\n",
    "display(frac_true_svc.head(5))\n",
    "print('-------------------------------------------')\n",
    "print('Common correct predictions:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_svc.loc[labels_svc.correct,'pred'].value_counts().head(5))\n",
    "display(frac_pred_svc.head(5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Abu Sayyaf Group (ASG): Frequently Predicted Wrongly\n",
    "\n",
    "A look at some of the features of ASG events, and the groups that are often mistaken for ASG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============================\n",
      "Abu Sayyaf Group (ASG)\n",
      "=============================\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Philippines    451\n",
       "Malaysia        19\n",
       "Name: country, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============================\n",
      "Philippines\n",
      "=============================\n",
      "New People's Army (NPA)                        2412\n",
      "Abu Sayyaf Group (ASG)                          451\n",
      "Moro Islamic Liberation Front (MILF)            363\n",
      "Bangsamoro Islamic Freedom Movement (BIFM)      320\n",
      "Moro National Liberation Front (MNLF)           196\n",
      "Communists                                       33\n",
      "April 6th Liberation Movement                    31\n",
      "Muslim Rebels                                    20\n",
      "Muslims                                          18\n",
      "Jemaah Islamiya (JI)                             18\n",
      "Maute Group                                      15\n",
      "Alex Boncayao Brigade (ABB)                      11\n",
      "Muslim Separatists                               10\n",
      "Muslim extremists                                 8\n",
      "Muslim Militants                                  8\n",
      "Islamic State of Iraq and the Levant (ISIL)       8\n",
      "Muslim Guerrillas                                 6\n",
      "Armed People                                      5\n",
      "Gunmen                                            4\n",
      "Vigilante Group                                   3\n",
      "Right-Wing Death Squad                            2\n",
      "Islamist extremists                               2\n",
      "Death Squad                                       2\n",
      "Rebels                                            2\n",
      "Pirates                                           2\n",
      "Left-wing extremists                              2\n",
      "Anti-Nuclear extremists                           1\n",
      "Right-Wing Group                                  1\n",
      "Students                                          1\n",
      "Guerrillas                                        1\n",
      "Terrorists                                        1\n",
      "Name: gname, dtype: int64\n",
      "=============================\n",
      "Malaysia\n",
      "=============================\n",
      "Abu Sayyaf Group (ASG)                         19\n",
      "Muslim Brotherhood                              1\n",
      "Communists                                      1\n",
      "Islamic State of Iraq and the Levant (ISIL)     1\n",
      "Name: gname, dtype: int64\n",
      "================================================\n",
      "Regularly Mistaken for Abu Sayyaf Group (ASG)\n",
      "================================================\n",
      "New People's Army (NPA)                        10\n",
      "Moro Islamic Liberation Front (MILF)           10\n",
      "Moro National Liberation Front (MNLF)           2\n",
      "Bangsamoro Islamic Freedom Movement (BIFM)      2\n",
      "Pirates                                         1\n",
      "Muslims                                         1\n",
      "Islamic State of Iraq and the Levant (ISIL)     1\n",
      "Name: true, dtype: int64\n",
      "================================================\n",
      "Features More Common in ASG than FARC\n",
      "================================================\n"
     ]
    },
    {
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       "      <th>Abu Sayyaf Group (ASG)</th>\n",
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       "      <th>country_Philippines</th>\n",
       "      <td>1469.487935</td>\n",
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       "      <th>country_Malaysia</th>\n",
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       "      <th>targsubtype1_Commercial Maritime</th>\n",
       "      <td>62.993374</td>\n",
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       "      <th>ransom_yes</th>\n",
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       "                                  Abu Sayyaf Group (ASG)  \\\n",
       "country_Philippines                          1469.487935   \n",
       "country_Malaysia                              122.122216   \n",
       "targsubtype1_Commercial Maritime               62.993374   \n",
       "targtype1_Maritime                             71.132873   \n",
       "ransom_yes                                    162.345198   \n",
       "\n",
       "                                  Revolutionary Armed Forces of Colombia (FARC)  \\\n",
       "country_Philippines                                                    0.000000   \n",
       "country_Malaysia                                                       0.000000   \n",
       "targsubtype1_Commercial Maritime                                       0.000000   \n",
       "targtype1_Maritime                                                    11.855479   \n",
       "ransom_yes                                                           119.274023   \n",
       "\n",
       "                                         diff  \n",
       "country_Philippines               1469.487935  \n",
       "country_Malaysia                   122.122216  \n",
       "targsubtype1_Commercial Maritime    62.993374  \n",
       "targtype1_Maritime                  59.277394  \n",
       "ransom_yes                          43.071175  "
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     "text": [
      "=========================================================================\n",
      "Features More Common FARC than ASG\n",
      "=========================================================================\n"
     ]
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       "      <th>Abu Sayyaf Group (ASG)</th>\n",
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       "    <tr>\n",
       "      <th>claimed_no</th>\n",
       "      <td>574.068632</td>\n",
       "      <td>3227.927996</td>\n",
       "      <td>-2653.859364</td>\n",
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       "    <tr>\n",
       "      <th>suicide_no</th>\n",
       "      <td>612.222999</td>\n",
       "      <td>3227.397786</td>\n",
       "      <td>-2615.174787</td>\n",
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       "    <tr>\n",
       "      <th>success_yes</th>\n",
       "      <td>546.645176</td>\n",
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       "    <tr>\n",
       "      <th>ishostkid_no</th>\n",
       "      <td>400.999229</td>\n",
       "      <td>2727.551362</td>\n",
       "      <td>-2326.552133</td>\n",
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       "                  Abu Sayyaf Group (ASG)  \\\n",
       "country_Colombia                0.000000   \n",
       "claimed_no                    574.068632   \n",
       "suicide_no                    612.222999   \n",
       "success_yes                   546.645176   \n",
       "ishostkid_no                  400.999229   \n",
       "\n",
       "                  Revolutionary Armed Forces of Colombia (FARC)         diff  \n",
       "country_Colombia                                    7730.303727 -7730.303727  \n",
       "claimed_no                                          3227.927996 -2653.859364  \n",
       "suicide_no                                          3227.397786 -2615.174787  \n",
       "success_yes                                         2958.315070 -2411.669894  \n",
       "ishostkid_no                                        2727.551362 -2326.552133  "
      ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================================================================\n",
      "Features Similar in Both\n",
      "=========================================================================\n"
     ]
    },
    {
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       "  <tbody>\n",
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       "      <th>targsubtype1_Religion Identified</th>\n",
       "      <td>3.652845</td>\n",
       "      <td>3.652845</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nperps_0</th>\n",
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       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>targsubtype1_Television Journalist/Staff/Facility</th>\n",
       "      <td>4.134148</td>\n",
       "      <td>4.134148</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Port</th>\n",
       "      <td>5.576532</td>\n",
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       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>targsubtype1_Marketplace/Plaza/Square</th>\n",
       "      <td>16.853982</td>\n",
       "      <td>16.853982</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weapsubtype1_Pressure Trigger</th>\n",
       "      <td>5.656574</td>\n",
       "      <td>5.656574</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>targsubtype1_Affiliated Institution</th>\n",
       "      <td>4.427909</td>\n",
       "      <td>4.427909</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>targsubtype1_Student</th>\n",
       "      <td>4.357291</td>\n",
       "      <td>4.357291</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>targsubtype1_Military Checkpoint</th>\n",
       "      <td>7.785972</td>\n",
       "      <td>7.785972</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Religious Figures/Institutions</th>\n",
       "      <td>40.596276</td>\n",
       "      <td>37.696542</td>\n",
       "      <td>2.899734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_School/University/Educational Building</th>\n",
       "      <td>24.733000</td>\n",
       "      <td>21.641375</td>\n",
       "      <td>3.091625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>suicide_yes</th>\n",
       "      <td>3.630622</td>\n",
       "      <td>7.261243</td>\n",
       "      <td>3.630622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weapsubtype1_Remote Trigger</th>\n",
       "      <td>40.181291</td>\n",
       "      <td>43.834136</td>\n",
       "      <td>3.652845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>attacktype1_Hijacking</th>\n",
       "      <td>18.735159</td>\n",
       "      <td>22.482191</td>\n",
       "      <td>3.747032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Teacher/Professor/Instructor</th>\n",
       "      <td>7.518909</td>\n",
       "      <td>11.278363</td>\n",
       "      <td>3.759454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Procession/Gathering (funeral, wedding, birthday, religious)</th>\n",
       "      <td>3.967094</td>\n",
       "      <td>7.934188</td>\n",
       "      <td>3.967094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_International NGO</th>\n",
       "      <td>8.028693</td>\n",
       "      <td>4.014347</td>\n",
       "      <td>4.014347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Tourist</th>\n",
       "      <td>25.621680</td>\n",
       "      <td>21.351400</td>\n",
       "      <td>4.270280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Educational Institution</th>\n",
       "      <td>36.961128</td>\n",
       "      <td>31.274800</td>\n",
       "      <td>5.686327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Public Area (garden, parking lot, garage, beach, public building, camp)</th>\n",
       "      <td>3.459350</td>\n",
       "      <td>10.378049</td>\n",
       "      <td>6.918700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_NGO</th>\n",
       "      <td>14.795319</td>\n",
       "      <td>22.192979</td>\n",
       "      <td>7.397660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Telephone/Telegraph</th>\n",
       "      <td>4.270280</td>\n",
       "      <td>12.810840</td>\n",
       "      <td>8.540560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hostkidoutcome_Hostage(s) escaped (not during rescue attempt)</th>\n",
       "      <td>13.357805</td>\n",
       "      <td>4.452602</td>\n",
       "      <td>8.905203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Domestic NGO</th>\n",
       "      <td>9.007790</td>\n",
       "      <td>18.015580</td>\n",
       "      <td>9.007790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Named Civilian</th>\n",
       "      <td>57.675176</td>\n",
       "      <td>66.781782</td>\n",
       "      <td>9.106607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Airport</th>\n",
       "      <td>3.921973</td>\n",
       "      <td>15.687893</td>\n",
       "      <td>11.765920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Vehicles/Transportation</th>\n",
       "      <td>18.323308</td>\n",
       "      <td>30.538847</td>\n",
       "      <td>12.215539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Election-related</th>\n",
       "      <td>8.540560</td>\n",
       "      <td>21.351400</td>\n",
       "      <td>12.810840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Newspaper Journalist/Staff/Facility</th>\n",
       "      <td>10.112389</td>\n",
       "      <td>23.595575</td>\n",
       "      <td>13.483186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Civilian Maritime</th>\n",
       "      <td>18.961135</td>\n",
       "      <td>4.740284</td>\n",
       "      <td>14.220851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nperps_11+</th>\n",
       "      <td>66.835523</td>\n",
       "      <td>384.972610</td>\n",
       "      <td>318.137087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ishostkid_yes</th>\n",
       "      <td>260.323817</td>\n",
       "      <td>610.493907</td>\n",
       "      <td>350.170090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Village/City/Town/Suburb</th>\n",
       "      <td>11.515163</td>\n",
       "      <td>382.879183</td>\n",
       "      <td>371.364020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Business</th>\n",
       "      <td>119.705263</td>\n",
       "      <td>493.784208</td>\n",
       "      <td>374.078946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nkill_1</th>\n",
       "      <td>89.843851</td>\n",
       "      <td>484.738914</td>\n",
       "      <td>394.895064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nwound_2to10</th>\n",
       "      <td>128.465976</td>\n",
       "      <td>606.527887</td>\n",
       "      <td>478.061911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Utilities</th>\n",
       "      <td>3.060077</td>\n",
       "      <td>498.792498</td>\n",
       "      <td>495.732422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targsubtype1_Military Unit/Patrol/Convoy</th>\n",
       "      <td>54.403961</td>\n",
       "      <td>552.629712</td>\n",
       "      <td>498.225751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>propextent_Minor (likely &lt; $1 million)</th>\n",
       "      <td>133.420610</td>\n",
       "      <td>644.171382</td>\n",
       "      <td>510.750772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Private Citizens &amp; Property</th>\n",
       "      <td>142.724571</td>\n",
       "      <td>703.428244</td>\n",
       "      <td>560.703673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Police</th>\n",
       "      <td>35.821563</td>\n",
       "      <td>620.160815</td>\n",
       "      <td>584.339252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>targtype1_Military</th>\n",
       "      <td>143.195111</td>\n",
       "      <td>734.452343</td>\n",
       "      <td>591.257232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_2010s</th>\n",
       "      <td>540.277598</td>\n",
       "      <td>1149.414106</td>\n",
       "      <td>609.136508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>property_no</th>\n",
       "      <td>359.327258</td>\n",
       "      <td>1095.653605</td>\n",
       "      <td>736.326348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weapsubtype1_Automatic Weapon</th>\n",
       "      <td>39.413397</td>\n",
       "      <td>871.731615</td>\n",
       "      <td>832.318217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_2000s</th>\n",
       "      <td>240.225479</td>\n",
       "      <td>1100.123501</td>\n",
       "      <td>859.898022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>attacktype1_Armed Assault</th>\n",
       "      <td>136.062158</td>\n",
       "      <td>1045.204758</td>\n",
       "      <td>909.142600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nkill_2to10</th>\n",
       "      <td>139.588775</td>\n",
       "      <td>1093.087484</td>\n",
       "      <td>953.498709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weaptype1_Firearms</th>\n",
       "      <td>301.812748</td>\n",
       "      <td>1265.993072</td>\n",
       "      <td>964.180324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_1990s</th>\n",
       "      <td>85.166381</td>\n",
       "      <td>1094.258950</td>\n",
       "      <td>1009.092569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>attacktype1_Bombing/Explosion</th>\n",
       "      <td>255.653812</td>\n",
       "      <td>1282.263652</td>\n",
       "      <td>1026.609839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weaptype1_Explosives/Bombs/Dynamite</th>\n",
       "      <td>268.768567</td>\n",
       "      <td>1329.906686</td>\n",
       "      <td>1061.138120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nkill_0</th>\n",
       "      <td>361.551337</td>\n",
       "      <td>1562.896521</td>\n",
       "      <td>1201.345184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ransom_no</th>\n",
       "      <td>110.564000</td>\n",
       "      <td>1736.859933</td>\n",
       "      <td>1626.295933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>property_yes</th>\n",
       "      <td>204.056524</td>\n",
       "      <td>2013.866253</td>\n",
       "      <td>1809.809730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nwound_0</th>\n",
       "      <td>347.208488</td>\n",
       "      <td>2178.116634</td>\n",
       "      <td>1830.908146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ishostkid_no</th>\n",
       "      <td>400.999229</td>\n",
       "      <td>2727.551362</td>\n",
       "      <td>2326.552133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>success_yes</th>\n",
       "      <td>546.645176</td>\n",
       "      <td>2958.315070</td>\n",
       "      <td>2411.669894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>suicide_no</th>\n",
       "      <td>612.222999</td>\n",
       "      <td>3227.397786</td>\n",
       "      <td>2615.174787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>claimed_no</th>\n",
       "      <td>574.068632</td>\n",
       "      <td>3227.927996</td>\n",
       "      <td>2653.859364</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>133 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Abu Sayyaf Group (ASG)  \\\n",
       "targsubtype1_Religion Identified                                  3.652845   \n",
       "nperps_0                                                          4.963427   \n",
       "targsubtype1_Television Journalist/Staff/Facility                 4.134148   \n",
       "targsubtype1_Port                                                 5.576532   \n",
       "targsubtype1_Marketplace/Plaza/Square                            16.853982   \n",
       "weapsubtype1_Pressure Trigger                                     5.656574   \n",
       "targsubtype1_Affiliated Institution                               4.427909   \n",
       "targsubtype1_Student                                              4.357291   \n",
       "targsubtype1_Military Checkpoint                                  7.785972   \n",
       "targtype1_Religious Figures/Institutions                         40.596276   \n",
       "targsubtype1_School/University/Educational Buil...               24.733000   \n",
       "suicide_yes                                                       3.630622   \n",
       "weapsubtype1_Remote Trigger                                      40.181291   \n",
       "attacktype1_Hijacking                                            18.735159   \n",
       "targsubtype1_Teacher/Professor/Instructor                         7.518909   \n",
       "targsubtype1_Procession/Gathering (funeral, wed...                3.967094   \n",
       "targsubtype1_International NGO                                    8.028693   \n",
       "targsubtype1_Tourist                                             25.621680   \n",
       "targtype1_Educational Institution                                36.961128   \n",
       "targsubtype1_Public Area (garden, parking lot, ...                3.459350   \n",
       "targtype1_NGO                                                    14.795319   \n",
       "targsubtype1_Telephone/Telegraph                                  4.270280   \n",
       "hostkidoutcome_Hostage(s) escaped (not during r...               13.357805   \n",
       "targsubtype1_Domestic NGO                                         9.007790   \n",
       "targsubtype1_Named Civilian                                      57.675176   \n",
       "targsubtype1_Airport                                              3.921973   \n",
       "targsubtype1_Vehicles/Transportation                             18.323308   \n",
       "targsubtype1_Election-related                                     8.540560   \n",
       "targsubtype1_Newspaper Journalist/Staff/Facility                 10.112389   \n",
       "targsubtype1_Civilian Maritime                                   18.961135   \n",
       "...                                                                    ...   \n",
       "nperps_11+                                                       66.835523   \n",
       "ishostkid_yes                                                   260.323817   \n",
       "targsubtype1_Village/City/Town/Suburb                            11.515163   \n",
       "targtype1_Business                                              119.705263   \n",
       "nkill_1                                                          89.843851   \n",
       "nwound_2to10                                                    128.465976   \n",
       "targtype1_Utilities                                               3.060077   \n",
       "targsubtype1_Military Unit/Patrol/Convoy                         54.403961   \n",
       "propextent_Minor (likely < $1 million)                          133.420610   \n",
       "targtype1_Private Citizens & Property                           142.724571   \n",
       "targtype1_Police                                                 35.821563   \n",
       "targtype1_Military                                              143.195111   \n",
       "year_2010s                                                      540.277598   \n",
       "property_no                                                     359.327258   \n",
       "weapsubtype1_Automatic Weapon                                    39.413397   \n",
       "year_2000s                                                      240.225479   \n",
       "attacktype1_Armed Assault                                       136.062158   \n",
       "nkill_2to10                                                     139.588775   \n",
       "weaptype1_Firearms                                              301.812748   \n",
       "year_1990s                                                       85.166381   \n",
       "attacktype1_Bombing/Explosion                                   255.653812   \n",
       "weaptype1_Explosives/Bombs/Dynamite                             268.768567   \n",
       "nkill_0                                                         361.551337   \n",
       "ransom_no                                                       110.564000   \n",
       "property_yes                                                    204.056524   \n",
       "nwound_0                                                        347.208488   \n",
       "ishostkid_no                                                    400.999229   \n",
       "success_yes                                                     546.645176   \n",
       "suicide_no                                                      612.222999   \n",
       "claimed_no                                                      574.068632   \n",
       "\n",
       "                                                    Revolutionary Armed Forces of Colombia (FARC)  \\\n",
       "targsubtype1_Religion Identified                                                         3.652845   \n",
       "nperps_0                                                                                 4.963427   \n",
       "targsubtype1_Television Journalist/Staff/Facility                                        4.134148   \n",
       "targsubtype1_Port                                                                        5.576532   \n",
       "targsubtype1_Marketplace/Plaza/Square                                                   16.853982   \n",
       "weapsubtype1_Pressure Trigger                                                            5.656574   \n",
       "targsubtype1_Affiliated Institution                                                      4.427909   \n",
       "targsubtype1_Student                                                                     4.357291   \n",
       "targsubtype1_Military Checkpoint                                                         7.785972   \n",
       "targtype1_Religious Figures/Institutions                                                37.696542   \n",
       "targsubtype1_School/University/Educational Buil...                                      21.641375   \n",
       "suicide_yes                                                                              7.261243   \n",
       "weapsubtype1_Remote Trigger                                                             43.834136   \n",
       "attacktype1_Hijacking                                                                   22.482191   \n",
       "targsubtype1_Teacher/Professor/Instructor                                               11.278363   \n",
       "targsubtype1_Procession/Gathering (funeral, wed...                                       7.934188   \n",
       "targsubtype1_International NGO                                                           4.014347   \n",
       "targsubtype1_Tourist                                                                    21.351400   \n",
       "targtype1_Educational Institution                                                       31.274800   \n",
       "targsubtype1_Public Area (garden, parking lot, ...                                      10.378049   \n",
       "targtype1_NGO                                                                           22.192979   \n",
       "targsubtype1_Telephone/Telegraph                                                        12.810840   \n",
       "hostkidoutcome_Hostage(s) escaped (not during r...                                       4.452602   \n",
       "targsubtype1_Domestic NGO                                                               18.015580   \n",
       "targsubtype1_Named Civilian                                                             66.781782   \n",
       "targsubtype1_Airport                                                                    15.687893   \n",
       "targsubtype1_Vehicles/Transportation                                                    30.538847   \n",
       "targsubtype1_Election-related                                                           21.351400   \n",
       "targsubtype1_Newspaper Journalist/Staff/Facility                                        23.595575   \n",
       "targsubtype1_Civilian Maritime                                                           4.740284   \n",
       "...                                                                                           ...   \n",
       "nperps_11+                                                                             384.972610   \n",
       "ishostkid_yes                                                                          610.493907   \n",
       "targsubtype1_Village/City/Town/Suburb                                                  382.879183   \n",
       "targtype1_Business                                                                     493.784208   \n",
       "nkill_1                                                                                484.738914   \n",
       "nwound_2to10                                                                           606.527887   \n",
       "targtype1_Utilities                                                                    498.792498   \n",
       "targsubtype1_Military Unit/Patrol/Convoy                                               552.629712   \n",
       "propextent_Minor (likely < $1 million)                                                 644.171382   \n",
       "targtype1_Private Citizens & Property                                                  703.428244   \n",
       "targtype1_Police                                                                       620.160815   \n",
       "targtype1_Military                                                                     734.452343   \n",
       "year_2010s                                                                            1149.414106   \n",
       "property_no                                                                           1095.653605   \n",
       "weapsubtype1_Automatic Weapon                                                          871.731615   \n",
       "year_2000s                                                                            1100.123501   \n",
       "attacktype1_Armed Assault                                                             1045.204758   \n",
       "nkill_2to10                                                                           1093.087484   \n",
       "weaptype1_Firearms                                                                    1265.993072   \n",
       "year_1990s                                                                            1094.258950   \n",
       "attacktype1_Bombing/Explosion                                                         1282.263652   \n",
       "weaptype1_Explosives/Bombs/Dynamite                                                   1329.906686   \n",
       "nkill_0                                                                               1562.896521   \n",
       "ransom_no                                                                             1736.859933   \n",
       "property_yes                                                                          2013.866253   \n",
       "nwound_0                                                                              2178.116634   \n",
       "ishostkid_no                                                                          2727.551362   \n",
       "success_yes                                                                           2958.315070   \n",
       "suicide_no                                                                            3227.397786   \n",
       "claimed_no                                                                            3227.927996   \n",
       "\n",
       "                                                           diff  \n",
       "targsubtype1_Religion Identified                       0.000000  \n",
       "nperps_0                                               0.000000  \n",
       "targsubtype1_Television Journalist/Staff/Facility      0.000000  \n",
       "targsubtype1_Port                                      0.000000  \n",
       "targsubtype1_Marketplace/Plaza/Square                  0.000000  \n",
       "weapsubtype1_Pressure Trigger                          0.000000  \n",
       "targsubtype1_Affiliated Institution                    0.000000  \n",
       "targsubtype1_Student                                   0.000000  \n",
       "targsubtype1_Military Checkpoint                       0.000000  \n",
       "targtype1_Religious Figures/Institutions               2.899734  \n",
       "targsubtype1_School/University/Educational Buil...     3.091625  \n",
       "suicide_yes                                            3.630622  \n",
       "weapsubtype1_Remote Trigger                            3.652845  \n",
       "attacktype1_Hijacking                                  3.747032  \n",
       "targsubtype1_Teacher/Professor/Instructor              3.759454  \n",
       "targsubtype1_Procession/Gathering (funeral, wed...     3.967094  \n",
       "targsubtype1_International NGO                         4.014347  \n",
       "targsubtype1_Tourist                                   4.270280  \n",
       "targtype1_Educational Institution                      5.686327  \n",
       "targsubtype1_Public Area (garden, parking lot, ...     6.918700  \n",
       "targtype1_NGO                                          7.397660  \n",
       "targsubtype1_Telephone/Telegraph                       8.540560  \n",
       "hostkidoutcome_Hostage(s) escaped (not during r...     8.905203  \n",
       "targsubtype1_Domestic NGO                              9.007790  \n",
       "targsubtype1_Named Civilian                            9.106607  \n",
       "targsubtype1_Airport                                  11.765920  \n",
       "targsubtype1_Vehicles/Transportation                  12.215539  \n",
       "targsubtype1_Election-related                         12.810840  \n",
       "targsubtype1_Newspaper Journalist/Staff/Facility      13.483186  \n",
       "targsubtype1_Civilian Maritime                        14.220851  \n",
       "...                                                         ...  \n",
       "nperps_11+                                           318.137087  \n",
       "ishostkid_yes                                        350.170090  \n",
       "targsubtype1_Village/City/Town/Suburb                371.364020  \n",
       "targtype1_Business                                   374.078946  \n",
       "nkill_1                                              394.895064  \n",
       "nwound_2to10                                         478.061911  \n",
       "targtype1_Utilities                                  495.732422  \n",
       "targsubtype1_Military Unit/Patrol/Convoy             498.225751  \n",
       "propextent_Minor (likely < $1 million)               510.750772  \n",
       "targtype1_Private Citizens & Property                560.703673  \n",
       "targtype1_Police                                     584.339252  \n",
       "targtype1_Military                                   591.257232  \n",
       "year_2010s                                           609.136508  \n",
       "property_no                                          736.326348  \n",
       "weapsubtype1_Automatic Weapon                        832.318217  \n",
       "year_2000s                                           859.898022  \n",
       "attacktype1_Armed Assault                            909.142600  \n",
       "nkill_2to10                                          953.498709  \n",
       "weaptype1_Firearms                                   964.180324  \n",
       "year_1990s                                          1009.092569  \n",
       "attacktype1_Bombing/Explosion                       1026.609839  \n",
       "weaptype1_Explosives/Bombs/Dynamite                 1061.138120  \n",
       "nkill_0                                             1201.345184  \n",
       "ransom_no                                           1626.295933  \n",
       "property_yes                                        1809.809730  \n",
       "nwound_0                                            1830.908146  \n",
       "ishostkid_no                                        2326.552133  \n",
       "success_yes                                         2411.669894  \n",
       "suicide_no                                          2615.174787  \n",
       "claimed_no                                          2653.859364  \n",
       "\n",
       "[133 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('=============================')\n",
    "print('Abu Sayyaf Group (ASG)')\n",
    "print('=============================')\n",
    "asg=df[df.gname=='Abu Sayyaf Group (ASG)']\n",
    "display(asg['country'].value_counts())\n",
    "\n",
    "print('=============================')\n",
    "print('Philippines')\n",
    "print('=============================')\n",
    "print(df[df.country == 'Philippines']['gname'].value_counts())\n",
    "\n",
    "print('=============================')\n",
    "print('Malaysia')\n",
    "print('=============================')\n",
    "print(df[df.country == 'Malaysia']['gname'].value_counts())\n",
    "\n",
    "print('================================================')\n",
    "print('Regularly Mistaken for Abu Sayyaf Group (ASG)')\n",
    "print('================================================')\n",
    "print(labels_svc.loc[(~labels_svc.correct) & (labels_svc.pred=='Abu Sayyaf Group (ASG)')].true.value_counts().head(10))\n",
    "\n",
    "asg_w = w_tfidf.loc['Abu Sayyaf Group (ASG)']\n",
    "farc_w = w_tfidf.loc['Revolutionary Armed Forces of Colombia (FARC)']\n",
    "asgfarc = pd.DataFrame({'Abu Sayyaf Group (ASG)':asg_w, 'Revolutionary Armed Forces of Colombia (FARC)':farc_w})\n",
    "asgfarc['diff'] = asgfarc['Abu Sayyaf Group (ASG)']-asgfarc['Revolutionary Armed Forces of Colombia (FARC)']\n",
    "\n",
    "print('================================================')\n",
    "print('Features More Common in ASG than FARC')\n",
    "print('================================================')\n",
    "display(asgfarc.sort_values('diff').tail(5).sort_values(by='diff',ascending=False))\n",
    "\n",
    "print('=========================================================================')\n",
    "print('Features More Common FARC than ASG')\n",
    "print('=========================================================================')\n",
    "display(asgfarc.sort_values('diff').head(5))\n",
    "\n",
    "print('=========================================================================')\n",
    "print('Features Similar in Both')\n",
    "print('=========================================================================')\n",
    "inboth = (asgfarc['Abu Sayyaf Group (ASG)']>0.005) & (asgfarc['Revolutionary Armed Forces of Colombia (FARC)']>0.005)\n",
    "display(abs(asgfarc.loc[inboth]).sort_values('diff'))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Countries of ASG Predicted Events\n",
    "\n",
    "ASG often predicted for events in countries they were never active in. Suggests country should be weighted much more heavily? Try much simpler model using only year, latitude, longitude?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======================================================================\n",
      "Countries of Events Incorrectly Predicted as Abu Sayyaf Group (ASG)\n",
      "======================================================================\n",
      "['Philippines' 'Malaysia']\n",
      "======================================================================\n",
      "Countries Where Abu Sayyaf Group (ASG) Carried Out Attacks\n",
      "======================================================================\n",
      "['Philippines' 'Malaysia']\n"
     ]
    }
   ],
   "source": [
    "# merge the predicted labels columns to the test_events df\n",
    "test_events_svc = pd.merge(df_test, \n",
    "                       pd.DataFrame({'pred':labels_svc_pred},index=df_test.index),\n",
    "                       left_index=True,right_index=True)\n",
    "\n",
    "test_events_svc['true'] = test_events_svc['gname']==test_events_svc['pred']\n",
    "\n",
    "print('======================================================================')\n",
    "print('Countries of Events Incorrectly Predicted as Abu Sayyaf Group (ASG)')\n",
    "print('======================================================================')\n",
    "print(test_events_svc[(test_events_svc.pred=='Abu Sayyaf Group (ASG)') & (~test_events_svc.true)]['country'].unique())\n",
    "print('======================================================================')\n",
    "print('Countries Where Abu Sayyaf Group (ASG) Carried Out Attacks')\n",
    "print('======================================================================')\n",
    "print(df[df.gname=='Abu Sayyaf Group (ASG)']['country'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Naive Bayes - train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "suicide_no      0.959971\n",
       "success_yes     0.916372\n",
       "ishostkid_no    0.903616\n",
       "claimed_no      0.830598\n",
       "nwound_0        0.577317\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Taliban                                             0.077845\n",
       "Shining Path (SL)                                   0.053171\n",
       "Islamic State of Iraq and the Levant (ISIL)         0.050857\n",
       "Farabundo Marti National Liberation Front (FMLN)    0.039090\n",
       "Irish Republican Army (IRA)                         0.031815\n",
       "Name: gname, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year_1970s</th>\n",
       "      <th>year_1980s</th>\n",
       "      <th>year_1990s</th>\n",
       "      <th>year_2000s</th>\n",
       "      <th>year_2010s</th>\n",
       "      <th>country_Afghanistan</th>\n",
       "      <th>country_Algeria</th>\n",
       "      <th>country_Andorra</th>\n",
       "      <th>country_Angola</th>\n",
       "      <th>country_Argentina</th>\n",
       "      <th>...</th>\n",
       "      <th>nhostkid_2to10</th>\n",
       "      <th>nhostkid_11+</th>\n",
       "      <th>ransom_no</th>\n",
       "      <th>ransom_yes</th>\n",
       "      <th>hostkidoutcome_Attempted Rescue</th>\n",
       "      <th>hostkidoutcome_Combination</th>\n",
       "      <th>hostkidoutcome_Hostage(s) escaped (not during rescue attempt)</th>\n",
       "      <th>hostkidoutcome_Hostage(s) killed (not during rescue attempt)</th>\n",
       "      <th>hostkidoutcome_Hostage(s) released by perpetrators</th>\n",
       "      <th>hostkidoutcome_Successful Rescue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16 January Organization for the Liberation of Tripoli</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20 December Movement (M-20)</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23rd of September Communist League</th>\n",
       "      <td>0.971429</td>\n",
       "      <td>0.028571</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.771429</td>\n",
       "      <td>0.228571</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.028571</td>\n",
       "      <td>0.114286</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2nd of June Movement</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.083333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31 January People's Front (FP-31)</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 367 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    year_1970s  year_1980s  \\\n",
       "16 January Organization for the Liberation of T...    0.000000    1.000000   \n",
       "20 December Movement (M-20)                           0.000000    0.000000   \n",
       "23rd of September Communist League                    0.971429    0.028571   \n",
       "2nd of June Movement                                  0.833333    0.166667   \n",
       "31 January People's Front (FP-31)                     0.000000    1.000000   \n",
       "\n",
       "                                                    year_1990s  year_2000s  \\\n",
       "16 January Organization for the Liberation of T...         0.0         0.0   \n",
       "20 December Movement (M-20)                                1.0         0.0   \n",
       "23rd of September Communist League                         0.0         0.0   \n",
       "2nd of June Movement                                       0.0         0.0   \n",
       "31 January People's Front (FP-31)                          0.0         0.0   \n",
       "\n",
       "                                                    year_2010s  \\\n",
       "16 January Organization for the Liberation of T...         0.0   \n",
       "20 December Movement (M-20)                                0.0   \n",
       "23rd of September Communist League                         0.0   \n",
       "2nd of June Movement                                       0.0   \n",
       "31 January People's Front (FP-31)                          0.0   \n",
       "\n",
       "                                                    country_Afghanistan  \\\n",
       "16 January Organization for the Liberation of T...                  0.0   \n",
       "20 December Movement (M-20)                                         0.0   \n",
       "23rd of September Communist League                                  0.0   \n",
       "2nd of June Movement                                                0.0   \n",
       "31 January People's Front (FP-31)                                   0.0   \n",
       "\n",
       "                                                    country_Algeria  \\\n",
       "16 January Organization for the Liberation of T...              0.0   \n",
       "20 December Movement (M-20)                                     0.0   \n",
       "23rd of September Communist League                              0.0   \n",
       "2nd of June Movement                                            0.0   \n",
       "31 January People's Front (FP-31)                               0.0   \n",
       "\n",
       "                                                    country_Andorra  \\\n",
       "16 January Organization for the Liberation of T...              0.0   \n",
       "20 December Movement (M-20)                                     0.0   \n",
       "23rd of September Communist League                              0.0   \n",
       "2nd of June Movement                                            0.0   \n",
       "31 January People's Front (FP-31)                               0.0   \n",
       "\n",
       "                                                    country_Angola  \\\n",
       "16 January Organization for the Liberation of T...             0.0   \n",
       "20 December Movement (M-20)                                    0.0   \n",
       "23rd of September Communist League                             0.0   \n",
       "2nd of June Movement                                           0.0   \n",
       "31 January People's Front (FP-31)                              0.0   \n",
       "\n",
       "                                                    country_Argentina  \\\n",
       "16 January Organization for the Liberation of T...                0.0   \n",
       "20 December Movement (M-20)                                       0.0   \n",
       "23rd of September Communist League                                0.0   \n",
       "2nd of June Movement                                              0.0   \n",
       "31 January People's Front (FP-31)                                 0.0   \n",
       "\n",
       "                                                                  ...                 \\\n",
       "16 January Organization for the Liberation of T...                ...                  \n",
       "20 December Movement (M-20)                                       ...                  \n",
       "23rd of September Communist League                                ...                  \n",
       "2nd of June Movement                                              ...                  \n",
       "31 January People's Front (FP-31)                                 ...                  \n",
       "\n",
       "                                                    nhostkid_2to10  \\\n",
       "16 January Organization for the Liberation of T...             0.0   \n",
       "20 December Movement (M-20)                                    0.0   \n",
       "23rd of September Communist League                             0.0   \n",
       "2nd of June Movement                                           0.0   \n",
       "31 January People's Front (FP-31)                              0.1   \n",
       "\n",
       "                                                    nhostkid_11+  ransom_no  \\\n",
       "16 January Organization for the Liberation of T...           0.0   1.000000   \n",
       "20 December Movement (M-20)                                  0.0   1.000000   \n",
       "23rd of September Communist League                           0.0   0.771429   \n",
       "2nd of June Movement                                         0.0   1.000000   \n",
       "31 January People's Front (FP-31)                            0.0   1.000000   \n",
       "\n",
       "                                                    ransom_yes  \\\n",
       "16 January Organization for the Liberation of T...    0.000000   \n",
       "20 December Movement (M-20)                           0.000000   \n",
       "23rd of September Communist League                    0.228571   \n",
       "2nd of June Movement                                  0.000000   \n",
       "31 January People's Front (FP-31)                     0.000000   \n",
       "\n",
       "                                                    hostkidoutcome_Attempted Rescue  \\\n",
       "16 January Organization for the Liberation of T...                              0.0   \n",
       "20 December Movement (M-20)                                                     0.0   \n",
       "23rd of September Communist League                                              0.0   \n",
       "2nd of June Movement                                                            0.0   \n",
       "31 January People's Front (FP-31)                                               0.0   \n",
       "\n",
       "                                                    hostkidoutcome_Combination  \\\n",
       "16 January Organization for the Liberation of T...                         0.0   \n",
       "20 December Movement (M-20)                                                0.0   \n",
       "23rd of September Communist League                                         0.0   \n",
       "2nd of June Movement                                                       0.0   \n",
       "31 January People's Front (FP-31)                                          0.0   \n",
       "\n",
       "                                                    hostkidoutcome_Hostage(s) escaped (not during rescue attempt)  \\\n",
       "16 January Organization for the Liberation of T...                                                0.0               \n",
       "20 December Movement (M-20)                                                                       0.0               \n",
       "23rd of September Communist League                                                                0.0               \n",
       "2nd of June Movement                                                                              0.0               \n",
       "31 January People's Front (FP-31)                                                                 0.0               \n",
       "\n",
       "                                                    hostkidoutcome_Hostage(s) killed (not during rescue attempt)  \\\n",
       "16 January Organization for the Liberation of T...                                           0.000000              \n",
       "20 December Movement (M-20)                                                                  0.000000              \n",
       "23rd of September Communist League                                                           0.028571              \n",
       "2nd of June Movement                                                                         0.083333              \n",
       "31 January People's Front (FP-31)                                                            0.000000              \n",
       "\n",
       "                                                    hostkidoutcome_Hostage(s) released by perpetrators  \\\n",
       "16 January Organization for the Liberation of T...                                           0.000000    \n",
       "20 December Movement (M-20)                                                                  0.000000    \n",
       "23rd of September Communist League                                                           0.114286    \n",
       "2nd of June Movement                                                                         0.000000    \n",
       "31 January People's Front (FP-31)                                                            0.000000    \n",
       "\n",
       "                                                    hostkidoutcome_Successful Rescue  \n",
       "16 January Organization for the Liberation of T...                               0.0  \n",
       "20 December Movement (M-20)                                                      0.0  \n",
       "23rd of September Communist League                                               0.0  \n",
       "2nd of June Movement                                                             0.0  \n",
       "31 January People's Front (FP-31)                                                0.0  \n",
       "\n",
       "[5 rows x 367 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# probability each feature value\n",
    "p_x = X_dum_train.sum()/len(X_dum_train)\n",
    "display(p_x.sort_values(ascending=False).head())\n",
    "\n",
    "# probability each group y\n",
    "grp_incs_train = y_train.value_counts()\n",
    "p_y = grp_incs_train/len(X_dum_train)\n",
    "display(p_y.head())\n",
    "\n",
    "# probability each feature value, given group y\n",
    "p_xgy = df_dum_train.groupby('gname').sum()\n",
    "p_xgy = p_xgy.divide(grp_incs_train, axis=0)\n",
    "display(p_xgy.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Naive Bayes - Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overall accuracy 0.609433667084\n"
     ]
    }
   ],
   "source": [
    "# series to store results in\n",
    "y_bayes = pd.Series(index=X_dum_test.index)\n",
    "\n",
    "for event in X_dum_test.index:\n",
    "    # likelihood for each feature given each group\n",
    "    probs = X_dum_test.loc[event]*p_xgy\n",
    "    \n",
    "    # multiply likelihoods for each feature\n",
    "    probs=probs.T\n",
    "    probs=probs[probs.sum(axis=1)>0]\n",
    "    probs=probs.product().multiply(p_y)\n",
    "    \n",
    "    # normalise\n",
    "    #probs = probs/probs.sum()\n",
    "    \n",
    "    # store group with max likelihood\n",
    "    y_bayes[event]=probs.idxmax(axis=1)\n",
    "    \n",
    "df_bayes = pd.DataFrame({'gname':y_test,'pred':y_bayes})\n",
    "df_bayes['true'] = df_bayes.gname == df_bayes.pred\n",
    "\n",
    "print('overall accuracy',sum(df_bayes.true)/len(df_bayes))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "precision 0.609433667084\n",
      "recall 0.609433667084\n",
      "accuracy 0.609433667084\n",
      "confusion matrix (top 20 grps):\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "      <td>447</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>289</td>\n",
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       "      <td>40</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>424</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>84</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>153</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>106</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>156</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>181</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>231</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>226</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>194</td>\n",
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       "      <th>19</th>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>188</td>\n",
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     "text": [
      "grp13:  National Liberation Army of Colombia (ELN)\n",
      "grp6:  Revolutionary Armed Forces of Colombia (FARC)\n",
      "----------------------------\n",
      "grp14:  Maoists\n",
      "grp11:  Communist Party of India - Maoist (CPI-Maoist)\n",
      "----------------------------\n",
      "grp19:  Houthi extremists (Ansar Allah)\n",
      "grp17:  Al-Qaida in the Arabian Peninsula (AQAP)\n",
      "----------------------------\n"
     ]
    }
   ],
   "source": [
    "print('precision',precision_score(df_bayes.gname, df_bayes.pred, labels=top_grps,average='micro'))\n",
    "print('recall',recall_score(df_bayes.gname, df_bayes.pred, labels=top_grps,average='micro'))\n",
    "print('accuracy',accuracy_score(df_bayes.gname, df_bayes.pred))\n",
    "print('confusion matrix (top 20 grps):')\n",
    "cmatrix = confusion_matrix(df_bayes.gname, df_bayes.pred,labels=top_grps)        \n",
    "display(pd.DataFrame(cmatrix).iloc[:20,:20])\n",
    "\n",
    "print('grp13: ',top_grps[13])\n",
    "print('grp6: ',top_grps[6])\n",
    "print('----------------------------')\n",
    "print('grp14: ',top_grps[14])\n",
    "print('grp11: ',top_grps[11])\n",
    "print('----------------------------')\n",
    "print('grp19: ',top_grps[19])\n",
    "print('grp17: ',top_grps[17])\n",
    "print('----------------------------')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sklearn Naive Bayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score: 0.611975907384\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import BernoulliNB\n",
    "clf = BernoulliNB()\n",
    "clf.fit(X_dum_train.fillna(0), y_train)\n",
    "\n",
    "y_NBgaus = clf.predict(X_dum_test.fillna(0))\n",
    "\n",
    "print('score:',accuracy_score(y_test,y_NBgaus))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Groups commonly labelled incorrectly:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Shining Path (SL)                                372\n",
       "Revolutionary Armed Forces of Colombia (FARC)    365\n",
       "Islamic State of Iraq and the Levant (ISIL)      309\n",
       "National Liberation Army of Colombia (ELN)       268\n",
       "New People's Army (NPA)                          237\n",
       "Name: true, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Young Communist League                      NaN\n",
       "Youths                                      NaN\n",
       "Zapatista National Liberation Army          NaN\n",
       "Zimbabwe African Nationalist Union (ZANU)   NaN\n",
       "Zimbabwe African People's Union             NaN\n",
       "Name: true, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Common incorrect predictions:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Death Squad                                       514\n",
       "Gunmen                                            320\n",
       "Lord's Resistance Army (LRA)                      297\n",
       "Communist Party of India - Maoist (CPI-Maoist)    291\n",
       "National Liberation Army of Colombia (ELN)        273\n",
       "Name: pred, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Omega-7                              NaN\n",
       "People's Liberation Front of India   NaN\n",
       "Prima Linea                          NaN\n",
       "Resistenza                           NaN\n",
       "Terrorists                           NaN\n",
       "Name: pred, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Groups commonly labelled correctly:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Taliban                                             1741\n",
       "Shining Path (SL)                                   1007\n",
       "Farabundo Marti National Liberation Front (FMLN)     963\n",
       "Islamic State of Iraq and the Levant (ISIL)          944\n",
       "Al-Shabaab                                           764\n",
       "Name: true, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Pro Hartal Activists                                0.966667\n",
       "Al-Gama'at al-Islamiyya (IG)                        0.948718\n",
       "African National Congress (South Africa)            0.948454\n",
       "Farabundo Marti National Liberation Front (FMLN)    0.945044\n",
       "Al-Shabaab                                          0.938575\n",
       "Name: true, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "Common correct predictions:\n",
      "-------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Taliban                                             1741\n",
       "Shining Path (SL)                                   1007\n",
       "Farabundo Marti National Liberation Front (FMLN)     963\n",
       "Islamic State of Iraq and the Levant (ISIL)          944\n",
       "Al-Shabaab                                           764\n",
       "Name: pred, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Zebra killers                                 1.0\n",
       "Tawhid and Jihad                              1.0\n",
       "National Liberation Army (NLA) (Macedonia)    1.0\n",
       "Popular Forces of April 25                    1.0\n",
       "Popular Revolutionary Bloc (BPR)              1.0\n",
       "Name: pred, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a data frame of labels and predictions\n",
    "labels_NBgaus = pd.DataFrame({'true':y_test.values, 'pred':y_NBgaus},index=y_test.index)\n",
    "\n",
    "# was the predcition correct?\n",
    "labels_NBgaus['correct'] = labels_NBgaus['pred']==labels_NBgaus['true']\n",
    "\n",
    "# labelled correctly / total events\n",
    "frac_true_NBgaus = (labels_NBgaus.loc[labels_NBgaus.correct,'true'].value_counts()/labels_NBgaus['true'].value_counts()).sort_values(ascending=False)\n",
    "\n",
    "# predicted correctly / predicted total\n",
    "frac_pred_NBgaus = (labels_NBgaus.loc[labels_NBgaus.correct,'pred'].value_counts()/labels_NBgaus['pred'].value_counts()).sort_values(ascending=False)\n",
    "\n",
    "\n",
    "print('-------------------------------------------')\n",
    "print('Groups commonly labelled incorrectly:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_NBgaus.loc[~labels_NBgaus.correct,'true'].value_counts().head(5))\n",
    "display(frac_true_NBgaus.tail(5).sort_values())\n",
    "print('-------------------------------------------')\n",
    "print('Common incorrect predictions:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_NBgaus.loc[~labels_NBgaus.correct,'pred'].value_counts().head(5))\n",
    "display(frac_pred_NBgaus.tail(5).sort_values())\n",
    "print('-------------------------------------------')\n",
    "print('Groups commonly labelled correctly:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_NBgaus.loc[labels_NBgaus.correct,'true'].value_counts().head(5))\n",
    "display(frac_true_NBgaus.head(5))\n",
    "print('-------------------------------------------')\n",
    "print('Common correct predictions:')\n",
    "print('-------------------------------------------')\n",
    "display(labels_NBgaus.loc[labels_NBgaus.correct,'pred'].value_counts().head(5))\n",
    "display(frac_pred_NBgaus.head(5))\n"
   ]
  }
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