• About the Project
  • Built With
• Getting Started
  • Prerequisites
  • Installation
• Usage
• License
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Implementatio of Empirical Analysis of Predictive Algorithms for Collaborative Filtering.

• The dataset I have used is a subset of the movie ratings data from the Netflix Prize.
• It contains a training set, a test set, a movies file, a dataset description file, and a README file.
• The training and test sets are both subsets of the Netflix training data.
• The evaluation metrics I have used are the Mean Absolute Error and the Root Mean Squared Error.

• Python 3.7

Lets see how to run this program on a local machine.

You will need the following modules

1 import sys
2 import warnings
3 from math import sqrt 
4 import os
5 import numpy as np 
6 import math
7 import numpy as np

1. Clone the repo

git clone https://github.com/Shivvrat/Collaborative-Filtering.git

Use the main.py to run the algorithm.

Please enter the following command line argument:-

python main.py [dataset_name]

Please use the following command line parameters for the main.py file :-

• Dataset name :-

Provide the name of folder for the dataset (please keep the folder in the same directory as the code only). Also the inside structure of the dataset folder should be same as that of given netflix folder.

Distributed under the MIT License. See LICENSE for more information.

Your Name - Shivvrat Arya@ShivvratA - [email protected]

Project Link: https://github.com/Shivvrat/Collaborative-Filtering.git