17_KMEANS - Detección de transacciones bancarias fraudulentas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/drive/1Ss7QNdkJ1OnQAtso-pXXp4scU7ED3rn4\">Abre este Jupyter en Google Colab</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Caso Práctico: KMEANS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conjunto de datos: Detección de transacciones bancarias fraudulentas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Descripción\n",
    "The datasets contains transactions made by credit cards in September 2013 by european cardholders. \n",
    "This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.\n",
    "\n",
    "It contains only numerical input variables which are the result of a PCA transformation. Unfortunately, due to confidentiality issues, we cannot provide the original features and more background information about the data. Features V1, V2, … V28 are the principal components obtained with PCA, the only features which have not been transformed with PCA are 'Time' and 'Amount'. Feature 'Time' contains the seconds elapsed between each transaction and the first transaction in the dataset. The feature 'Amount' is the transaction Amount, this feature can be used for example-dependant cost-senstive learning. Feature 'Class' is the response variable and it takes value 1 in case of fraud and 0 otherwise.\n",
    "\n",
    "### Descarga de los ficheros de datos\n",
    "https://www.kaggle.com/mlg-ulb/creditcardfraud#creditcard.csv\n",
    "\n",
    "### Referencias adicionales sobre el conjunto de datos\n",
    "_The dataset has been collected and analysed during a research collaboration of Worldline and the Machine Learning Group (http://mlg.ulb.ac.be) of ULB (Université Libre de Bruxelles) on big data mining and fraud detection.\n",
    "More details on current and past projects on related topics are available on https://www.researchgate.net/project/Fraud-detection-5 and the page of the DefeatFraud project._"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: seaborn in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (0.13.2)\n",
      "Requirement already satisfied: numpy!=1.24.0,>=1.20 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from seaborn) (1.26.3)\n",
      "Requirement already satisfied: pandas>=1.2 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from seaborn) (2.2.0)\n",
      "Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from seaborn) (3.8.2)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.2.0)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (4.47.2)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.4.5)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (23.1)\n",
      "Requirement already satisfied: pillow>=8 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (10.2.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (3.1.1)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from pandas>=1.2->seaborn) (2023.3.post1)\n",
      "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from pandas>=1.2->seaborn) (2023.4)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\santiago\\anaconda3\\envs\\machinelearning\\lib\\site-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.4->seaborn) (1.16.0)\n"
     ]
    }
   ],
   "source": [
    "# Instalamos seaborn\n",
    "!pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.gridspec as gridspec\n",
    "from collections import Counter\n",
    "from sklearn import metrics\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "# Ignoramos algunos warnings que se producen por invocar el modelo sin el nombre de las características\n",
    "warnings.filterwarnings('ignore', category=UserWarning, message='.*X does not have valid feature names.*')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Funciones auxiliares"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Original code: https://bit.ly/2TNHBZ5\n",
    "def plot_data(X, y):\n",
    "    plt.plot(X[:, 0][y==0], X[:, 1][y==0], 'k.', markersize=2)\n",
    "    plt.plot(X[:, 0][y==1], X[:, 1][y==1], 'r.', markersize=2)\n",
    "\n",
    "def plot_centroids(centroids, weights=None, circle_color='w', cross_color='k'):\n",
    "    if weights is not None:\n",
    "        centroids = centroids[weights > weights.max() / 10]\n",
    "    plt.scatter(centroids[:, 0], centroids[:, 1],\n",
    "                marker='o', s=30, linewidths=8,\n",
    "                color=circle_color, zorder=10, alpha=0.9)\n",
    "    plt.scatter(centroids[:, 0], centroids[:, 1],\n",
    "                marker='x', s=50, linewidths=50,\n",
    "                color=cross_color, zorder=11, alpha=1)\n",
    "\n",
    "def plot_decision_boundaries(clusterer, X, y, resolution=1000, show_centroids=True):\n",
    "    mins = X.min(axis=0) - 0.1\n",
    "    maxs = X.max(axis=0) + 0.1\n",
    "    xx, yy = np.meshgrid(np.linspace(mins[0], maxs[0], resolution),\n",
    "                         np.linspace(mins[1], maxs[1], resolution))\n",
    "    Z = clusterer.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "\n",
    "    plt.contourf(Z, extent=(mins[0], maxs[0], mins[1], maxs[1]),\n",
    "                cmap=\"Pastel2\")\n",
    "    plt.contour(Z, extent=(mins[0], maxs[0], mins[1], maxs[1]),\n",
    "                linewidths=1, colors='k')\n",
    "    plot_data(X, y)\n",
    "    if show_centroids:\n",
    "        plot_centroids(clusterer.cluster_centers_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def purity_score(y_true, y_pred):\n",
    "    # compute contingency matrix (also called confusion matrix)\n",
    "    contingency_matrix = metrics.cluster.contingency_matrix(y_true, y_pred)\n",
    "    # return purity\n",
    "    return np.sum(np.amax(contingency_matrix, axis=0)) / np.sum(contingency_matrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Lectura del conjunto de datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"datasets/creditcard.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Visualización del conjunto de datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>Time</th>\n",
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       "      <td>-0.055353</td>\n",
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      "text/plain": [
       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
       "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "5   2.0 -0.425966  0.960523  1.141109 -0.168252  0.420987 -0.029728  0.476201   \n",
       "6   4.0  1.229658  0.141004  0.045371  1.202613  0.191881  0.272708 -0.005159   \n",
       "7   7.0 -0.644269  1.417964  1.074380 -0.492199  0.948934  0.428118  1.120631   \n",
       "8   7.0 -0.894286  0.286157 -0.113192 -0.271526  2.669599  3.721818  0.370145   \n",
       "9   9.0 -0.338262  1.119593  1.044367 -0.222187  0.499361 -0.246761  0.651583   \n",
       "\n",
       "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
       "0  0.098698  0.363787  ... -0.018307  0.277838 -0.110474  0.066928  0.128539   \n",
       "1  0.085102 -0.255425  ... -0.225775 -0.638672  0.101288 -0.339846  0.167170   \n",
       "2  0.247676 -1.514654  ...  0.247998  0.771679  0.909412 -0.689281 -0.327642   \n",
       "3  0.377436 -1.387024  ... -0.108300  0.005274 -0.190321 -1.175575  0.647376   \n",
       "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
       "5  0.260314 -0.568671  ... -0.208254 -0.559825 -0.026398 -0.371427 -0.232794   \n",
       "6  0.081213  0.464960  ... -0.167716 -0.270710 -0.154104 -0.780055  0.750137   \n",
       "7 -3.807864  0.615375  ...  1.943465 -1.015455  0.057504 -0.649709 -0.415267   \n",
       "8  0.851084 -0.392048  ... -0.073425 -0.268092 -0.204233  1.011592  0.373205   \n",
       "9  0.069539 -0.736727  ... -0.246914 -0.633753 -0.120794 -0.385050 -0.069733   \n",
       "\n",
       "        V26       V27       V28  Amount  Class  \n",
       "0 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.125895 -0.008983  0.014724    2.69      0  \n",
       "2 -0.139097 -0.055353 -0.059752  378.66      0  \n",
       "3 -0.221929  0.062723  0.061458  123.50      0  \n",
       "4  0.502292  0.219422  0.215153   69.99      0  \n",
       "5  0.105915  0.253844  0.081080    3.67      0  \n",
       "6 -0.257237  0.034507  0.005168    4.99      0  \n",
       "7 -0.051634 -1.206921 -1.085339   40.80      0  \n",
       "8 -0.384157  0.011747  0.142404   93.20      0  \n",
       "9  0.094199  0.246219  0.083076    3.68      0  \n",
       "\n",
       "[10 rows x 31 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Número de características: 31\n",
      "Longitud del conjunto de datos: 284807\n"
     ]
    }
   ],
   "source": [
    "print(\"Número de características:\", len(df.columns))\n",
    "print(\"Longitud del conjunto de datos:\", len(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Class\n",
       "0    284315\n",
       "1       492\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 492 transacciones fraudulentas, 284315 transacciones legitimas\n",
    "# El conjunto de datos se encuntra desequilabrado\n",
    "df[\"Class\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 284807 entries, 0 to 284806\n",
      "Data columns (total 31 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   Time    284807 non-null  float64\n",
      " 1   V1      284807 non-null  float64\n",
      " 2   V2      284807 non-null  float64\n",
      " 3   V3      284807 non-null  float64\n",
      " 4   V4      284807 non-null  float64\n",
      " 5   V5      284807 non-null  float64\n",
      " 6   V6      284807 non-null  float64\n",
      " 7   V7      284807 non-null  float64\n",
      " 8   V8      284807 non-null  float64\n",
      " 9   V9      284807 non-null  float64\n",
      " 10  V10     284807 non-null  float64\n",
      " 11  V11     284807 non-null  float64\n",
      " 12  V12     284807 non-null  float64\n",
      " 13  V13     284807 non-null  float64\n",
      " 14  V14     284807 non-null  float64\n",
      " 15  V15     284807 non-null  float64\n",
      " 16  V16     284807 non-null  float64\n",
      " 17  V17     284807 non-null  float64\n",
      " 18  V18     284807 non-null  float64\n",
      " 19  V19     284807 non-null  float64\n",
      " 20  V20     284807 non-null  float64\n",
      " 21  V21     284807 non-null  float64\n",
      " 22  V22     284807 non-null  float64\n",
      " 23  V23     284807 non-null  float64\n",
      " 24  V24     284807 non-null  float64\n",
      " 25  V25     284807 non-null  float64\n",
      " 26  V26     284807 non-null  float64\n",
      " 27  V27     284807 non-null  float64\n",
      " 28  V28     284807 non-null  float64\n",
      " 29  Amount  284807 non-null  float64\n",
      " 30  Class   284807 non-null  int64  \n",
      "dtypes: float64(30), int64(1)\n",
      "memory usage: 67.4 MB\n"
     ]
    }
   ],
   "source": [
    "# Visualizamos los tipos de cada uno de los atributos\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time      False\n",
       "V1        False\n",
       "V2        False\n",
       "V3        False\n",
       "V4        False\n",
       "V5        False\n",
       "V6        False\n",
       "V7        False\n",
       "V8        False\n",
       "V9        False\n",
       "V10       False\n",
       "V11       False\n",
       "V12       False\n",
       "V13       False\n",
       "V14       False\n",
       "V15       False\n",
       "V16       False\n",
       "V17       False\n",
       "V18       False\n",
       "V19       False\n",
       "V20       False\n",
       "V21       False\n",
       "V22       False\n",
       "V23       False\n",
       "V24       False\n",
       "V25       False\n",
       "V26       False\n",
       "V27       False\n",
       "V28       False\n",
       "Amount    False\n",
       "Class     False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Comprobamos si alguna columna tiene valores nulos\n",
    "df.isna().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>284807.000000</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>284807.000000</td>\n",
       "      <td>284807.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>94813.859575</td>\n",
       "      <td>1.168375e-15</td>\n",
       "      <td>3.416908e-16</td>\n",
       "      <td>-1.379537e-15</td>\n",
       "      <td>2.074095e-15</td>\n",
       "      <td>9.604066e-16</td>\n",
       "      <td>1.487313e-15</td>\n",
       "      <td>-5.556467e-16</td>\n",
       "      <td>1.213481e-16</td>\n",
       "      <td>-2.406331e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>1.654067e-16</td>\n",
       "      <td>-3.568593e-16</td>\n",
       "      <td>2.578648e-16</td>\n",
       "      <td>4.473266e-15</td>\n",
       "      <td>5.340915e-16</td>\n",
       "      <td>1.683437e-15</td>\n",
       "      <td>-3.660091e-16</td>\n",
       "      <td>-1.227390e-16</td>\n",
       "      <td>88.349619</td>\n",
       "      <td>0.001727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>47488.145955</td>\n",
       "      <td>1.958696e+00</td>\n",
       "      <td>1.651309e+00</td>\n",
       "      <td>1.516255e+00</td>\n",
       "      <td>1.415869e+00</td>\n",
       "      <td>1.380247e+00</td>\n",
       "      <td>1.332271e+00</td>\n",
       "      <td>1.237094e+00</td>\n",
       "      <td>1.194353e+00</td>\n",
       "      <td>1.098632e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>7.345240e-01</td>\n",
       "      <td>7.257016e-01</td>\n",
       "      <td>6.244603e-01</td>\n",
       "      <td>6.056471e-01</td>\n",
       "      <td>5.212781e-01</td>\n",
       "      <td>4.822270e-01</td>\n",
       "      <td>4.036325e-01</td>\n",
       "      <td>3.300833e-01</td>\n",
       "      <td>250.120109</td>\n",
       "      <td>0.041527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-5.640751e+01</td>\n",
       "      <td>-7.271573e+01</td>\n",
       "      <td>-4.832559e+01</td>\n",
       "      <td>-5.683171e+00</td>\n",
       "      <td>-1.137433e+02</td>\n",
       "      <td>-2.616051e+01</td>\n",
       "      <td>-4.355724e+01</td>\n",
       "      <td>-7.321672e+01</td>\n",
       "      <td>-1.343407e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.483038e+01</td>\n",
       "      <td>-1.093314e+01</td>\n",
       "      <td>-4.480774e+01</td>\n",
       "      <td>-2.836627e+00</td>\n",
       "      <td>-1.029540e+01</td>\n",
       "      <td>-2.604551e+00</td>\n",
       "      <td>-2.256568e+01</td>\n",
       "      <td>-1.543008e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>54201.500000</td>\n",
       "      <td>-9.203734e-01</td>\n",
       "      <td>-5.985499e-01</td>\n",
       "      <td>-8.903648e-01</td>\n",
       "      <td>-8.486401e-01</td>\n",
       "      <td>-6.915971e-01</td>\n",
       "      <td>-7.682956e-01</td>\n",
       "      <td>-5.540759e-01</td>\n",
       "      <td>-2.086297e-01</td>\n",
       "      <td>-6.430976e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.283949e-01</td>\n",
       "      <td>-5.423504e-01</td>\n",
       "      <td>-1.618463e-01</td>\n",
       "      <td>-3.545861e-01</td>\n",
       "      <td>-3.171451e-01</td>\n",
       "      <td>-3.269839e-01</td>\n",
       "      <td>-7.083953e-02</td>\n",
       "      <td>-5.295979e-02</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>84692.000000</td>\n",
       "      <td>1.810880e-02</td>\n",
       "      <td>6.548556e-02</td>\n",
       "      <td>1.798463e-01</td>\n",
       "      <td>-1.984653e-02</td>\n",
       "      <td>-5.433583e-02</td>\n",
       "      <td>-2.741871e-01</td>\n",
       "      <td>4.010308e-02</td>\n",
       "      <td>2.235804e-02</td>\n",
       "      <td>-5.142873e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.945017e-02</td>\n",
       "      <td>6.781943e-03</td>\n",
       "      <td>-1.119293e-02</td>\n",
       "      <td>4.097606e-02</td>\n",
       "      <td>1.659350e-02</td>\n",
       "      <td>-5.213911e-02</td>\n",
       "      <td>1.342146e-03</td>\n",
       "      <td>1.124383e-02</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>139320.500000</td>\n",
       "      <td>1.315642e+00</td>\n",
       "      <td>8.037239e-01</td>\n",
       "      <td>1.027196e+00</td>\n",
       "      <td>7.433413e-01</td>\n",
       "      <td>6.119264e-01</td>\n",
       "      <td>3.985649e-01</td>\n",
       "      <td>5.704361e-01</td>\n",
       "      <td>3.273459e-01</td>\n",
       "      <td>5.971390e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.863772e-01</td>\n",
       "      <td>5.285536e-01</td>\n",
       "      <td>1.476421e-01</td>\n",
       "      <td>4.395266e-01</td>\n",
       "      <td>3.507156e-01</td>\n",
       "      <td>2.409522e-01</td>\n",
       "      <td>9.104512e-02</td>\n",
       "      <td>7.827995e-02</td>\n",
       "      <td>77.165000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>172792.000000</td>\n",
       "      <td>2.454930e+00</td>\n",
       "      <td>2.205773e+01</td>\n",
       "      <td>9.382558e+00</td>\n",
       "      <td>1.687534e+01</td>\n",
       "      <td>3.480167e+01</td>\n",
       "      <td>7.330163e+01</td>\n",
       "      <td>1.205895e+02</td>\n",
       "      <td>2.000721e+01</td>\n",
       "      <td>1.559499e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.720284e+01</td>\n",
       "      <td>1.050309e+01</td>\n",
       "      <td>2.252841e+01</td>\n",
       "      <td>4.584549e+00</td>\n",
       "      <td>7.519589e+00</td>\n",
       "      <td>3.517346e+00</td>\n",
       "      <td>3.161220e+01</td>\n",
       "      <td>3.384781e+01</td>\n",
       "      <td>25691.160000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Time            V1            V2            V3            V4  \\\n",
       "count  284807.000000  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean    94813.859575  1.168375e-15  3.416908e-16 -1.379537e-15  2.074095e-15   \n",
       "std     47488.145955  1.958696e+00  1.651309e+00  1.516255e+00  1.415869e+00   \n",
       "min         0.000000 -5.640751e+01 -7.271573e+01 -4.832559e+01 -5.683171e+00   \n",
       "25%     54201.500000 -9.203734e-01 -5.985499e-01 -8.903648e-01 -8.486401e-01   \n",
       "50%     84692.000000  1.810880e-02  6.548556e-02  1.798463e-01 -1.984653e-02   \n",
       "75%    139320.500000  1.315642e+00  8.037239e-01  1.027196e+00  7.433413e-01   \n",
       "max    172792.000000  2.454930e+00  2.205773e+01  9.382558e+00  1.687534e+01   \n",
       "\n",
       "                 V5            V6            V7            V8            V9  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean   9.604066e-16  1.487313e-15 -5.556467e-16  1.213481e-16 -2.406331e-15   \n",
       "std    1.380247e+00  1.332271e+00  1.237094e+00  1.194353e+00  1.098632e+00   \n",
       "min   -1.137433e+02 -2.616051e+01 -4.355724e+01 -7.321672e+01 -1.343407e+01   \n",
       "25%   -6.915971e-01 -7.682956e-01 -5.540759e-01 -2.086297e-01 -6.430976e-01   \n",
       "50%   -5.433583e-02 -2.741871e-01  4.010308e-02  2.235804e-02 -5.142873e-02   \n",
       "75%    6.119264e-01  3.985649e-01  5.704361e-01  3.273459e-01  5.971390e-01   \n",
       "max    3.480167e+01  7.330163e+01  1.205895e+02  2.000721e+01  1.559499e+01   \n",
       "\n",
       "       ...           V21           V22           V23           V24  \\\n",
       "count  ...  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean   ...  1.654067e-16 -3.568593e-16  2.578648e-16  4.473266e-15   \n",
       "std    ...  7.345240e-01  7.257016e-01  6.244603e-01  6.056471e-01   \n",
       "min    ... -3.483038e+01 -1.093314e+01 -4.480774e+01 -2.836627e+00   \n",
       "25%    ... -2.283949e-01 -5.423504e-01 -1.618463e-01 -3.545861e-01   \n",
       "50%    ... -2.945017e-02  6.781943e-03 -1.119293e-02  4.097606e-02   \n",
       "75%    ...  1.863772e-01  5.285536e-01  1.476421e-01  4.395266e-01   \n",
       "max    ...  2.720284e+01  1.050309e+01  2.252841e+01  4.584549e+00   \n",
       "\n",
       "                V25           V26           V27           V28         Amount  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  284807.000000   \n",
       "mean   5.340915e-16  1.683437e-15 -3.660091e-16 -1.227390e-16      88.349619   \n",
       "std    5.212781e-01  4.822270e-01  4.036325e-01  3.300833e-01     250.120109   \n",
       "min   -1.029540e+01 -2.604551e+00 -2.256568e+01 -1.543008e+01       0.000000   \n",
       "25%   -3.171451e-01 -3.269839e-01 -7.083953e-02 -5.295979e-02       5.600000   \n",
       "50%    1.659350e-02 -5.213911e-02  1.342146e-03  1.124383e-02      22.000000   \n",
       "75%    3.507156e-01  2.409522e-01  9.104512e-02  7.827995e-02      77.165000   \n",
       "max    7.519589e+00  3.517346e+00  3.161220e+01  3.384781e+01   25691.160000   \n",
       "\n",
       "               Class  \n",
       "count  284807.000000  \n",
       "mean        0.001727  \n",
       "std         0.041527  \n",
       "min         0.000000  \n",
       "25%         0.000000  \n",
       "50%         0.000000  \n",
       "75%         0.000000  \n",
       "max         1.000000  \n",
       "\n",
       "[8 rows x 31 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x3200 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Representamos gráficamente las características\n",
    "features = df.drop(\"Class\", axis=1)\n",
    "\n",
    "plt.figure(figsize=(12, 32))\n",
    "gs = gridspec.GridSpec(8, 4)\n",
    "gs.update(hspace=0.8)\n",
    "\n",
    "for i, f in enumerate(features):\n",
    "    ax = plt.subplot(gs[i])\n",
    "    # Usando histplot para los casos donde Class == 1\n",
    "    sns.histplot(data=df[df[\"Class\"] == 1], x=f, kde=True, color=\"red\", stat=\"density\", label=\"Fraud\", alpha=0.5)\n",
    "    # Usando histplot para los casos donde Class == 0\n",
    "    sns.histplot(data=df[df[\"Class\"] == 0], x=f, kde=True, color=\"blue\", stat=\"density\", label=\"Legit\", alpha=0.5)\n",
    "    ax.set_xlabel('')\n",
    "    ax.set_title(f\"Feature: {f}\")\n",
    "    ax.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Representación gráfica de dos características\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.scatter(df[\"V10\"][df['Class'] == 0], df[\"V14\"][df['Class'] == 0], c=\"g\", marker=\".\")\n",
    "plt.scatter(df[\"V10\"][df['Class'] == 1], df[\"V14\"][df['Class'] == 1], c=\"r\", marker=\".\")\n",
    "plt.xlabel(\"V10\", fontsize=14)\n",
    "plt.ylabel(\"V14\", fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Preparación del conjunto de datos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para este tipo de algoritmos es importante que todos los datos se encuentren en un rango similar, por lo tanto, podemos aplicar una función de escalado o normalización. Otra opción, es eliminar las características que no se encuentran en un rango similar siempre y cuando no sean muy influyentes para la predicción."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop([\"Time\", \"Amount\"], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Kmeans con un conjunto de datos de dos dimensiones"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Antes de comenzar con el entrenamiento de KMEANS para todos los atributos del conjunto de datos, se realiza una prueba para dos atributos con el objetivo de comprender como construye el límite de decisión."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>V10</th>\n",
       "      <th>V14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.090794</td>\n",
       "      <td>-0.311169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.166974</td>\n",
       "      <td>-0.143772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.207643</td>\n",
       "      <td>-0.165946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.054952</td>\n",
       "      <td>-0.287924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.753074</td>\n",
       "      <td>-1.119670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284802</th>\n",
       "      <td>4.356170</td>\n",
       "      <td>4.626942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284803</th>\n",
       "      <td>-0.975926</td>\n",
       "      <td>-0.675143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284804</th>\n",
       "      <td>-0.484782</td>\n",
       "      <td>-0.510602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284805</th>\n",
       "      <td>-0.399126</td>\n",
       "      <td>0.449624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284806</th>\n",
       "      <td>-0.915427</td>\n",
       "      <td>-0.084316</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>284807 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             V10       V14\n",
       "0       0.090794 -0.311169\n",
       "1      -0.166974 -0.143772\n",
       "2       0.207643 -0.165946\n",
       "3      -0.054952 -0.287924\n",
       "4       0.753074 -1.119670\n",
       "...          ...       ...\n",
       "284802  4.356170  4.626942\n",
       "284803 -0.975926 -0.675143\n",
       "284804 -0.484782 -0.510602\n",
       "284805 -0.399126  0.449624\n",
       "284806 -0.915427 -0.084316\n",
       "\n",
       "[284807 rows x 2 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df[[\"V10\", \"V14\"]].copy()\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generamos los clusters para nuestro conjunto de datos sin etiquetar\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=5, random_state=42)\n",
    "clusters = kmeans.fit_predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plot_decision_boundaries(kmeans, X.values, df[\"Class\"].values)\n",
    "plt.xlabel(\"V10\", fontsize=14)\n",
    "plt.ylabel(\"V14\", fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label 0 has 48659 samples - 6 are malicious samples\n",
      "Label 1 has 5631 samples - 429 are malicious samples\n",
      "Label 2 has 121724 samples - 18 are malicious samples\n",
      "Label 3 has 27404 samples - 8 are malicious samples\n",
      "Label 4 has 81389 samples - 31 are malicious samples\n"
     ]
    }
   ],
   "source": [
    "counter = Counter(clusters.tolist())\n",
    "bad_counter = Counter(clusters[df['Class'] == 1].tolist())\n",
    "\n",
    "for key in sorted(counter.keys()):\n",
    "    print(\"Label {0} has {1} samples - {2} are malicious samples\".format(\n",
    "        key, counter[key], bad_counter[key]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Kmeans con un conjunto de datos multidimensional"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Al tratarse de un algoritmo basado en aprendizaje no supervisado, no se requieren las etiquetas para entrenar o predir. Hay que tener en cuenta que en este tipo de problemas se presupone que no se dispone de las etiquetas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop(\"Class\", axis=1)\n",
    "y = df[\"Class\"].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=5, random_state=42)\n",
    "clusters = kmeans.fit_predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label 0 has 44522 samples - 228 are malicious samples\n",
      "Label 1 has 100946 samples - 81 are malicious samples\n",
      "Label 2 has 17163 samples - 0 are malicious samples\n",
      "Label 3 has 3630 samples - 129 are malicious samples\n",
      "Label 4 has 118546 samples - 54 are malicious samples\n"
     ]
    }
   ],
   "source": [
    "# Evaluamos los clusters y el contenido que se han formado\n",
    "counter = Counter(clusters.tolist())\n",
    "bad_counter = Counter(clusters[y == 1].tolist())\n",
    "\n",
    "for key in sorted(counter.keys()):\n",
    "    print(\"Label {0} has {1} samples - {2} are malicious samples\".format(\n",
    "        key, counter[key], bad_counter[key]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Reducción del número de características"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En muchas ocasiones Kmeans funciona mejor con un número de características bajo."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Aplicamos selección de características con _Random Forest_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(n_estimators=50, n_jobs=-1, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(n_estimators=50, n_jobs=-1, random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestClassifier(n_estimators=50, n_jobs=-1, random_state=42)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Utilizamos Random Forest para realizar selección de características\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "clf_rnd = RandomForestClassifier(n_estimators=50, random_state=42, n_jobs=-1)\n",
    "clf_rnd.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Seleccionamos las características más importantes\n",
    "feature_importances = {name: score for name, score in zip(list(df), clf_rnd.feature_importances_)}\n",
    "feature_importances_sorted = pd.Series(feature_importances).sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reducimos el conjunto de datos a las 7 características más importantes\n",
    "X_reduced = X[list(feature_importances_sorted.head(7).index)].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>V17</th>\n",
       "      <th>V14</th>\n",
       "      <th>V16</th>\n",
       "      <th>V12</th>\n",
       "      <th>V10</th>\n",
       "      <th>V11</th>\n",
       "      <th>V18</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.207971</td>\n",
       "      <td>-0.311169</td>\n",
       "      <td>-0.470401</td>\n",
       "      <td>-0.617801</td>\n",
       "      <td>0.090794</td>\n",
       "      <td>-0.551600</td>\n",
       "      <td>0.025791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.114805</td>\n",
       "      <td>-0.143772</td>\n",
       "      <td>0.463917</td>\n",
       "      <td>1.065235</td>\n",
       "      <td>-0.166974</td>\n",
       "      <td>1.612727</td>\n",
       "      <td>-0.183361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.109969</td>\n",
       "      <td>-0.165946</td>\n",
       "      <td>-2.890083</td>\n",
       "      <td>0.066084</td>\n",
       "      <td>0.207643</td>\n",
       "      <td>0.624501</td>\n",
       "      <td>-0.121359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.684093</td>\n",
       "      <td>-0.287924</td>\n",
       "      <td>-1.059647</td>\n",
       "      <td>0.178228</td>\n",
       "      <td>-0.054952</td>\n",
       "      <td>-0.226487</td>\n",
       "      <td>1.965775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.237033</td>\n",
       "      <td>-1.119670</td>\n",
       "      <td>-0.451449</td>\n",
       "      <td>0.538196</td>\n",
       "      <td>0.753074</td>\n",
       "      <td>-0.822843</td>\n",
       "      <td>-0.038195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284802</th>\n",
       "      <td>1.991691</td>\n",
       "      <td>4.626942</td>\n",
       "      <td>1.107641</td>\n",
       "      <td>2.711941</td>\n",
       "      <td>4.356170</td>\n",
       "      <td>-1.593105</td>\n",
       "      <td>0.510632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284803</th>\n",
       "      <td>-0.025693</td>\n",
       "      <td>-0.675143</td>\n",
       "      <td>-0.711757</td>\n",
       "      <td>0.915802</td>\n",
       "      <td>-0.975926</td>\n",
       "      <td>-0.150189</td>\n",
       "      <td>-1.221179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284804</th>\n",
       "      <td>0.313502</td>\n",
       "      <td>-0.510602</td>\n",
       "      <td>0.140716</td>\n",
       "      <td>0.063119</td>\n",
       "      <td>-0.484782</td>\n",
       "      <td>0.411614</td>\n",
       "      <td>0.395652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284805</th>\n",
       "      <td>0.509928</td>\n",
       "      <td>0.449624</td>\n",
       "      <td>-0.608577</td>\n",
       "      <td>-0.962886</td>\n",
       "      <td>-0.399126</td>\n",
       "      <td>-1.933849</td>\n",
       "      <td>1.113981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284806</th>\n",
       "      <td>-0.660377</td>\n",
       "      <td>-0.084316</td>\n",
       "      <td>-0.302620</td>\n",
       "      <td>-0.031513</td>\n",
       "      <td>-0.915427</td>\n",
       "      <td>-1.040458</td>\n",
       "      <td>0.167430</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>284807 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             V17       V14       V16       V12       V10       V11       V18\n",
       "0       0.207971 -0.311169 -0.470401 -0.617801  0.090794 -0.551600  0.025791\n",
       "1      -0.114805 -0.143772  0.463917  1.065235 -0.166974  1.612727 -0.183361\n",
       "2       1.109969 -0.165946 -2.890083  0.066084  0.207643  0.624501 -0.121359\n",
       "3      -0.684093 -0.287924 -1.059647  0.178228 -0.054952 -0.226487  1.965775\n",
       "4      -0.237033 -1.119670 -0.451449  0.538196  0.753074 -0.822843 -0.038195\n",
       "...          ...       ...       ...       ...       ...       ...       ...\n",
       "284802  1.991691  4.626942  1.107641  2.711941  4.356170 -1.593105  0.510632\n",
       "284803 -0.025693 -0.675143 -0.711757  0.915802 -0.975926 -0.150189 -1.221179\n",
       "284804  0.313502 -0.510602  0.140716  0.063119 -0.484782  0.411614  0.395652\n",
       "284805  0.509928  0.449624 -0.608577 -0.962886 -0.399126 -1.933849  1.113981\n",
       "284806 -0.660377 -0.084316 -0.302620 -0.031513 -0.915427 -1.040458  0.167430\n",
       "\n",
       "[284807 rows x 7 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_reduced"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Entrenamiento de KMEANS con el conjunto de datos reducido"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=5, random_state=42)\n",
    "clusters = kmeans.fit_predict(X_reduced)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label 0 has 109253 samples - 19 are malicious samples\n",
      "Label 1 has 124538 samples - 17 are malicious samples\n",
      "Label 2 has 30408 samples - 161 are malicious samples\n",
      "Label 3 has 308 samples - 265 are malicious samples\n",
      "Label 4 has 20300 samples - 30 are malicious samples\n"
     ]
    }
   ],
   "source": [
    "# Evaluamos los clusters y el contenido que se han formado\n",
    "counter = Counter(clusters.tolist())\n",
    "bad_counter = Counter(clusters[y == 1].tolist())\n",
    "\n",
    "for key in sorted(counter.keys()):\n",
    "    print(\"Label {0} has {1} samples - {2} are malicious samples\".format(\n",
    "        key, counter[key], bad_counter[key]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Evaluación de los resultados"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hay que tener cuidado con los conjuntos de datos desequilibrados cuando se utilizan métricas para medir la pureza de los clusters. Una posible solución es utilizar técnicas de equilibrado del conjunto de datos, como la generación de más ejemplos de transacciones fraudulentas o la disminución de ejemplos de transacciones legítimas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Purity Score: 0.9990519895929524\n"
     ]
    }
   ],
   "source": [
    "# Calculamos el purity score, es importante darse cuenta de que recibe las etiquetas\n",
    "print(\"Purity Score:\", purity_score(y, clusters))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shiloutte:  0.179227883887052\n"
     ]
    }
   ],
   "source": [
    "# Calculamos el coeficiente de Shiloutte, es importante darse cuenta de que no le pasamos las etiquetas\n",
    "print(\"Shiloutte: \", metrics.silhouette_score(X_reduced, clusters, sample_size=10000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calinski harabasz:  38466.001407022675\n"
     ]
    }
   ],
   "source": [
    "# Calculamos el Calinski harabasz score, es importante darse cuenta de que no le pasamos las etiquetas\n",
    "print(\"Calinski harabasz: \", metrics.calinski_harabasz_score(X_reduced, clusters))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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