Merge pull request #54 from tharoosha/dev_rate

Dev rate

.gitignore

@@ -27,3 +27,9 @@ npm-debug.log*
 yarn-debug.log*
 yarn-error.log*
 
+
+backend/ml_models/dataset.py
+backend/ml_models/recommanded_system/myenv
+backend/ml_models/recommanded_system/datset.py
+
+myenv

backend/.gitignore

@@ -24,3 +24,5 @@ npm-debug.log*
 yarn-debug.log*
 yarn-error.log*
 
+myenv
+

backend/ml_models/recommanded_system/train.csv

@@ -0,0 +1,266 @@
+video_title,video_description,video_category,video_rating
+Video 1,Description for Video 1,Trailers,4.5
+Video 2,Description for Video 2,Comedy,4.5
+Video 3,Description for Video 3,Thriller,4.1
+Video 4,Description for Video 4,People & Blogs,4.7
+Video 5,Description for Video 5,Sci-Fi/Fantasy,3.0
+Video 6,Description for Video 6,Gaming,3.8
+Video 7,Description for Video 7,Shorts,3.6
+Video 8,Description for Video 8,People & Blogs,4.7
+Video 9,Description for Video 9,Shows,2.3
+Video 10,Description for Video 10,Videoblogging,3.2
+Video 11,Description for Video 11,Sports,2.7
+Video 12,Description for Video 12,Nonprofits & Activism,4.2
+Video 13,Description for Video 13,Film & Animation,4.7
+Video 14,Description for Video 14,Thriller,3.4
+Video 15,Description for Video 15,Comedy,3.5
+Video 16,Description for Video 16,Thriller,3.9
+Video 17,Description for Video 17,Music,2.4
+Video 18,Description for Video 18,Foreign,2.6
+Video 19,Description for Video 19,Horror,4.0
+Video 20,Description for Video 20,People & Blogs,2.5
+Video 21,Description for Video 21,Drama,4.0
+Video 22,Description for Video 22,Education,3.6
+Video 23,Description for Video 23,Nonprofits & Activism,3.3
+Video 24,Description for Video 24,Science & Technology,4.2
+Video 25,Description for Video 25,Movies,3.5
+Video 26,Description for Video 26,Action/Adventure,4.5
+Video 27,Description for Video 27,Music,3.6
+Video 28,Description for Video 28,Comedy,3.5
+Video 29,Description for Video 29,Documentary,2.7
+Video 30,Description for Video 30,Movies,3.9
+Video 31,Description for Video 31,Movies,3.2
+Video 32,Description for Video 32,Gaming,4.9
+Video 33,Description for Video 33,Science & Technology,2.5
+Video 34,Description for Video 34,Comedy,3.4
+Video 35,Description for Video 35,Howto & Style,4.9
+Video 36,Description for Video 36,Howto & Style,2.6
+Video 37,Description for Video 37,Autos & Vehicles,2.4
+Video 38,Description for Video 38,Documentary,3.2
+Video 39,Description for Video 39,Classics,3.9
+Video 40,Description for Video 40,Music,4.9
+Video 41,Description for Video 41,Education,4.2
+Video 42,Description for Video 42,News & Politics,4.6
+Video 43,Description for Video 43,Autos & Vehicles,2.9
+Video 44,Description for Video 44,Action/Adventure,2.9
+Video 45,Description for Video 45,Anime/Animation,4.5
+Video 46,Description for Video 46,Sci-Fi/Fantasy,4.9
+Video 47,Description for Video 47,Gaming,4.3
+Video 48,Description for Video 48,Family,3.9
+Video 49,Description for Video 49,Classics,4.2
+Video 50,Description for Video 50,Nonprofits & Activism,4.2
+Video 51,Description for Video 51,Sci-Fi/Fantasy,3.0
+Video 52,Description for Video 52,Anime/Animation,4.8
+Video 53,Description for Video 53,People & Blogs,2.9
+Video 54,Description for Video 54,Horror,3.6
+Video 55,Description for Video 55,Entertainment,3.3
+Video 56,Description for Video 56,Family,4.6
+Video 57,Description for Video 57,Movies,3.0
+Video 58,Description for Video 58,Movies,2.2
+Video 59,Description for Video 59,Comedy,3.2
+Video 60,Description for Video 60,Comedy,3.7
+Video 61,Description for Video 61,Shorts,3.8
+Video 62,Description for Video 62,Anime/Animation,2.5
+Video 63,Description for Video 63,Sci-Fi/Fantasy,2.8
+Video 64,Description for Video 64,Family,4.2
+Video 65,Description for Video 65,Travel & Events,3.4
+Video 66,Description for Video 66,Family,3.2
+Video 67,Description for Video 67,Shows,2.1
+Video 68,Description for Video 68,Music,3.2
+Video 69,Description for Video 69,Entertainment,2.2
+Video 70,Description for Video 70,Comedy,3.5
+Video 71,Description for Video 71,News & Politics,3.7
+Video 72,Description for Video 72,Trailers,2.6
+Video 73,Description for Video 73,Entertainment,4.7
+Video 74,Description for Video 74,Anime/Animation,2.7
+Video 75,Description for Video 75,News & Politics,3.9
+Video 76,Description for Video 76,News & Politics,4.4
+Video 77,Description for Video 77,Sci-Fi/Fantasy,3.2
+Video 78,Description for Video 78,Howto & Style,3.0
+Video 79,Description for Video 79,Gaming,3.0
+Video 80,Description for Video 80,People & Blogs,4.7
+Video 81,Description for Video 81,Gaming,2.0
+Video 82,Description for Video 82,Nonprofits & Activism,2.0
+Video 83,Description for Video 83,Film & Animation,4.6
+Video 84,Description for Video 84,Pets & Animals,2.7
+Video 85,Description for Video 85,Travel & Events,3.8
+Video 86,Description for Video 86,Travel & Events,3.9
+Video 87,Description for Video 87,Education,2.4
+Video 88,Description for Video 88,Drama,2.1
+Video 89,Description for Video 89,Education,2.4
+Video 90,Description for Video 90,Comedy,2.3
+Video 91,Description for Video 91,Shorts,3.4
+Video 92,Description for Video 92,Nonprofits & Activism,4.3
+Video 93,Description for Video 93,Anime/Animation,4.0
+Video 94,Description for Video 94,Howto & Style,4.3
+Video 95,Description for Video 95,Film & Animation,2.2
+Video 96,Description for Video 96,Videoblogging,3.9
+Video 97,Description for Video 97,Nonprofits & Activism,3.4
+Video 98,Description for Video 98,Howto & Style,4.6
+Video 99,Description for Video 99,Science & Technology,3.1
+Video 100,Description for Video 100,Trailers,3.5
+Video 101,Description for Video 101,Gaming,3.7
+Video 102,Description for Video 102,Science & Technology,2.7
+Video 103,Description for Video 103,Anime/Animation,2.1
+Video 104,Description for Video 104,Movies,3.8
+Video 105,Description for Video 105,Shorts,2.1
+Video 106,Description for Video 106,Sports,5.0
+Video 107,Description for Video 107,Anime/Animation,4.9
+Video 108,Description for Video 108,Thriller,2.6
+Video 109,Description for Video 109,Documentary,2.8
+Video 110,Description for Video 110,Howto & Style,2.3
+Video 111,Description for Video 111,Education,3.6
+Video 112,Description for Video 112,Drama,3.1
+Video 113,Description for Video 113,Anime/Animation,4.0
+Video 114,Description for Video 114,Foreign,3.0
+Video 115,Description for Video 115,Classics,2.4
+Video 116,Description for Video 116,Shorts,4.8
+Video 117,Description for Video 117,Comedy,3.4
+Video 118,Description for Video 118,Drama,4.9
+Video 119,Description for Video 119,Foreign,3.1
+Video 120,Description for Video 120,Howto & Style,4.6
+Video 121,Description for Video 121,Sci-Fi/Fantasy,2.1
+Video 122,Description for Video 122,Education,2.1
+Video 123,Description for Video 123,Movies,3.5
+Video 124,Description for Video 124,Science & Technology,2.2
+Video 125,Description for Video 125,People & Blogs,4.5
+Video 126,Description for Video 126,Travel & Events,3.3
+Video 127,Description for Video 127,Entertainment,4.2
+Video 128,Description for Video 128,People & Blogs,2.3
+Video 129,Description for Video 129,Drama,3.6
+Video 130,Description for Video 130,Classics,2.6
+Video 131,Description for Video 131,Trailers,2.7
+Video 132,Description for Video 132,Autos & Vehicles,3.4
+Video 133,Description for Video 133,Horror,4.2
+Video 134,Description for Video 134,Nonprofits & Activism,4.4
+Video 135,Description for Video 135,Sci-Fi/Fantasy,4.1
+Video 136,Description for Video 136,Gaming,2.9
+Video 137,Description for Video 137,Autos & Vehicles,3.7
+Video 138,Description for Video 138,Family,4.1
+Video 139,Description for Video 139,Howto & Style,4.0
+Video 140,Description for Video 140,Gaming,2.7
+Video 141,Description for Video 141,Foreign,3.0
+Video 142,Description for Video 142,Drama,2.9
+Video 143,Description for Video 143,Gaming,3.1
+Video 144,Description for Video 144,Horror,3.0
+Video 145,Description for Video 145,News & Politics,3.7
+Video 146,Description for Video 146,Drama,2.5
+Video 147,Description for Video 147,Sci-Fi/Fantasy,2.8
+Video 148,Description for Video 148,Family,3.2
+Video 149,Description for Video 149,Foreign,3.5
+Video 150,Description for Video 150,Music,4.9
+Video 151,Description for Video 151,Thriller,2.7
+Video 152,Description for Video 152,Entertainment,2.4
+Video 153,Description for Video 153,Music,2.5
+Video 154,Description for Video 154,News & Politics,3.5
+Video 155,Description for Video 155,Science & Technology,3.1
+Video 156,Description for Video 156,News & Politics,2.5
+Video 157,Description for Video 157,Music,3.1
+Video 158,Description for Video 158,Comedy,3.8
+Video 159,Description for Video 159,Pets & Animals,2.7
+Video 160,Description for Video 160,Nonprofits & Activism,3.4
+Video 161,Description for Video 161,Anime/Animation,4.8
+Video 162,Description for Video 162,Videoblogging,5.0
+Video 163,Description for Video 163,Action/Adventure,3.1
+Video 164,Description for Video 164,Foreign,2.3
+Video 165,Description for Video 165,Sports,3.1
+Video 166,Description for Video 166,Documentary,4.3
+Video 167,Description for Video 167,Thriller,4.0
+Video 168,Description for Video 168,Horror,4.6
+Video 169,Description for Video 169,Thriller,2.2
+Video 170,Description for Video 170,Film & Animation,2.5
+Video 171,Description for Video 171,Shorts,2.2
+Video 172,Description for Video 172,Videoblogging,2.1
+Video 173,Description for Video 173,Documentary,4.5
+Video 174,Description for Video 174,Comedy,3.1
+Video 175,Description for Video 175,Education,2.4
+Video 176,Description for Video 176,Trailers,3.6
+Video 177,Description for Video 177,Drama,3.5
+Video 178,Description for Video 178,Shows,3.1
+Video 179,Description for Video 179,Shorts,3.7
+Video 180,Description for Video 180,Videoblogging,3.9
+Video 181,Description for Video 181,Sports,4.0
+Video 182,Description for Video 182,Action/Adventure,3.6
+Video 183,Description for Video 183,Sports,4.9
+Video 184,Description for Video 184,Autos & Vehicles,3.7
+Video 185,Description for Video 185,Shorts,2.1
+Video 186,Description for Video 186,Comedy,2.8
+Video 187,Description for Video 187,Travel & Events,2.1
+Video 188,Description for Video 188,News & Politics,4.1
+Video 189,Description for Video 189,Film & Animation,2.2
+Video 190,Description for Video 190,Shorts,5.0
+Video 191,Description for Video 191,Trailers,3.6
+Video 192,Description for Video 192,Gaming,2.8
+Video 193,Description for Video 193,Videoblogging,2.7
+Video 194,Description for Video 194,Horror,4.6
+Video 195,Description for Video 195,Trailers,2.6
+Video 196,Description for Video 196,Shows,4.8
+Video 197,Description for Video 197,Foreign,3.6
+Video 198,Description for Video 198,Family,3.5
+Video 199,Description for Video 199,Music,4.3
+Video 200,Description for Video 200,Sci-Fi/Fantasy,4.8
+Video 201,Description for Video 201,Shorts,3.6
+Video 202,Description for Video 202,Comedy,4.1
+Video 203,Description for Video 203,Comedy,2.1
+Video 204,Description for Video 204,Anime/Animation,4.0
+Video 205,Description for Video 205,Comedy,2.7
+Video 206,Description for Video 206,News & Politics,2.7
+Video 207,Description for Video 207,Howto & Style,3.5
+Video 208,Description for Video 208,Documentary,5.0
+Video 209,Description for Video 209,Sports,4.5
+Video 210,Description for Video 210,Howto & Style,3.4
+Video 211,Description for Video 211,Comedy,2.8
+Video 212,Description for Video 212,Science & Technology,2.3
+Video 213,Description for Video 213,Family,2.1
+Video 214,Description for Video 214,Science & Technology,2.5
+Video 215,Description for Video 215,Gaming,4.1
+Video 216,Description for Video 216,People & Blogs,2.3
+Video 217,Description for Video 217,Documentary,3.7
+Video 218,Description for Video 218,Shows,2.7
+Video 219,Description for Video 219,Drama,3.4
+Video 220,Description for Video 220,Movies,3.8
+Video 221,Description for Video 221,Autos & Vehicles,2.3
+Video 222,Description for Video 222,Family,4.3
+Video 223,Description for Video 223,Nonprofits & Activism,3.7
+Video 224,Description for Video 224,Education,2.2
+Video 225,Description for Video 225,Science & Technology,3.3
+Video 226,Description for Video 226,Entertainment,2.7
+Video 227,Description for Video 227,Documentary,2.9
+Video 228,Description for Video 228,Entertainment,3.7
+Video 229,Description for Video 229,Pets & Animals,4.6
+Video 230,Description for Video 230,Howto & Style,2.9
+Video 231,Description for Video 231,Autos & Vehicles,5.0
+Video 232,Description for Video 232,Gaming,4.4
+Video 233,Description for Video 233,Education,4.8
+Video 234,Description for Video 234,Foreign,3.6
+Video 235,Description for Video 235,Trailers,4.0
+Video 236,Description for Video 236,Science & Technology,4.1
+Video 237,Description for Video 237,Travel & Events,4.6
+Video 238,Description for Video 238,Documentary,3.6
+Video 239,Description for Video 239,Videoblogging,4.9
+Video 240,Description for Video 240,Classics,4.8
+Video 241,Description for Video 241,Travel & Events,3.5
+Video 242,Description for Video 242,Nonprofits & Activism,4.6
+Video 243,Description for Video 243,Movies,2.8
+Video 244,Description for Video 244,Foreign,4.8
+Video 245,Description for Video 245,Travel & Events,4.3
+Video 246,Description for Video 246,Film & Animation,3.7
+Video 247,Description for Video 247,Shorts,3.7
+Video 248,Description for Video 248,Pets & Animals,3.1
+Video 249,Description for Video 249,Nonprofits & Activism,3.5
+Video 250,Description for Video 250,Thriller,3.2
+Video 251,Description for Video 251,Comedy,4.6
+Video 252,Description for Video 252,Shorts,2.0
+Video 253,Description for Video 253,Nonprofits & Activism,4.2
+Video 254,Description for Video 254,Shorts,4.8
+Video 255,Description for Video 255,Comedy,3.8
+Video 256,Description for Video 256,Anime/Animation,4.3
+Video 257,Description for Video 257,People & Blogs,4.4
+Video 258,Description for Video 258,Shows,3.9
+Video 259,Description for Video 259,Music,3.1
+Video 260,Description for Video 260,Nonprofits & Activism,5.0
+Video 261,Description for Video 261,Gaming,3.3
+Video 262,Description for Video 262,Classics,2.8
+Video 263,Description for Video 263,Autos & Vehicles,2.3
+Video 264,Description for Video 264,Comedy,3.9
+Video 265,Description for Video 265,Pets & Animals,2.7

backend/ml_models/recommanded_system/video_by_rate.py

@@ -0,0 +1,115 @@
+# import pandas as pd
+# from sklearn.model_selection import train_test_split
+# from sklearn.linear_model import LinearRegression
+# from sklearn.metrics import mean_squared_error
+# from sklearn.feature_extraction.text import TfidfVectorizer
+# from sklearn.compose import ColumnTransformer
+# from sklearn.pipeline import Pipeline
+# from sklearn.preprocessing import OneHotEncoder
+# from sklearn.neighbors import NearestNeighbors
+
+# # Read the data from the CSV file
+# df = pd.read_csv('sample_dataset.csv')
+
+# # Define the features (text and categorical)
+# text_features = ['video_description']
+# categorical_features = ['video_category']
+
+# # Create a ColumnTransformer to preprocess text and categorical features
+# preprocessor = ColumnTransformer(
+#     transformers=[
+#         ('text', TfidfVectorizer(), text_features),
+#         ('cat', OneHotEncoder(), categorical_features)
+#     ])
+
+# # Create a Linear Regression model
+# model = Pipeline([
+#     ('preprocessor', preprocessor),
+#     ('regressor', LinearRegression())
+# ])
+
+# # Define the target variable
+# y = df['video_rating']
+
+
+# # Split the data into training and testing sets
+# X_train, X_test, y_train, y_test = train_test_split(df.drop('video_rating', axis=1), y, test_size=0.2, random_state=42)
+
+
+# # Convert column names to strings
+# X_train.columns = X_train.columns.astype(str)
+
+
+# # Train the model
+# model.fit(X_train, y_train)
+
+# # Make predictions
+# y_pred = model.predict(X_test)
+
+# # Calculate the Mean Squared Error
+# mse = mean_squared_error(y_test, y_pred)
+# print("Mean Squared Error:", mse)
+
+# # Now, you can use this model to recommend videos to a user based on their mood and rating preferences.
+# # To recommend videos for a user with mood "Shorts" and ratings between 3.5 and 4.0, you can use k-Nearest Neighbors (k-NN) to find the most similar videos.
+
+# # First, transform the user's mood and rating into the feature space used by the model
+# user_features = tfidf_vectorizer.transform(["Shorts"]).toarray()
+# user_rating = 3.75  # Average of 3.5 and 4.0
+
+# # Combine the user's features with their rating
+# user_input = pd.concat([pd.DataFrame(user_features), df[category_feature_names].iloc[0, :], pd.DataFrame({'user_rating': [user_rating]})], axis=1)
+
+# # Fit a k-NN model to find similar videos
+# knn = NearestNeighbors(n_neighbors=10)
+# knn.fit(X)
+
+# # Find the indices of the most similar videos
+# distances, indices = knn.kneighbors(user_input, n_neighbors=10)
+
+# # Get the recommended video titles
+# recommended_video_titles = df['video_title'].iloc[indices[0]]
+
+# print("Recommended videos:")
+# print(recommended_video_titles)
+
+
+import pandas as pd
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import linear_kernel
+
+# Step 1: Load the dataset
+df = pd.read_csv('train.csv')
+
+
+tfidf_vectorizer = TfidfVectorizer()
+tfidf_matrix = tfidf_vectorizer.fit_transform(df['video_description'])
+
+cosine_sim = linear_kernel(tfidf_matrix, tfidf_matrix)
+
+
+# Step 6: Make Predictions
+def get_recommendations(category, rating):
+    # Find the index of the video matching the user's input
+    user_input_index = df[(df['video_category'] == category) & (df['video_rating'] == rating)].index[0]
+
+    # Compute the cosine similarity scores for all videos
+    sim_scores = list(enumerate(cosine_sim[user_input_index]))
+
+    # Sort the videos based on similarity scores
+    sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True)
+
+    # Get the top recommendations
+    top_recommendations = sim_scores[1:6]  # Exclude the user's input video
+    recommended_indices = [rec[0] for rec in top_recommendations]
+
+    # Return the video titles of the recommended videos
+    recommended_titles = df['video_title'].iloc[recommended_indices]
+    return recommended_titles
+
+# Example usage
+user_category = "Comedy"
+user_rating = 3.4
+recommendations = get_recommendations(user_category, user_rating)
+print("Recommended Video Titles:")
+print(recommendations)