First commit and my first modification

README.txt

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+Readme
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+I have written three codes, one for user-based collaborative filtering, second for item-based collaborative filtering and the third for hybrid-based collaborative filtering.
+
+First, move to the folder and copy the files ratings.csv, toBeRated.csv, users.csv, and movies.csv to the downloaded “Code” folder. Now, enter the commands explained as follows:
+
+1. User-Based Collaborative Filtering:
+python userBased.py ratings.csv toBeRated.csv cosine jaccard pearson
+
+After the above command finish executing, it will provide result1.csv as the output file which will have the predicted ratings. Also, rmse_user.txt will be an output which shows the rmse obtained in all the three types of similarity and also shows which one is the best.
+
+2. Item-Based Collaborative Filtering:
+python itemBased.py ratings.csv toBeRated.csv cosine jaccard pearson
+
+After the above command finish executing, it will provide result2.csv as the output file which will have the predicted ratings. Also, rmse_item.txt will be an output which shows the rmse obtained in all the three types of similarity and also shows which one is the best.
+
+3. Hybrid-Based Collaborative Filtering:
+python hybrid.py ratings.csv toBeRated.csv users.csv movies.csv cosine jaccard pearson
+
+After the above command finish executing, it will provide result3.csv as the output file which will have the predicted ratings. Also, rmse_hybrid.txt will be an output which shows the rmse obtained in all the three types of similarity and also shows which one is the best.
+
+Author: Revant Kumar <[email protected]>