yash2998chhabria / CSE272-Recommendation_System

Basic Recommendation System built Using Suprise Module

Collaborative Filtering Implemented Using Single Value Decomposition

Evaluation Metrics:

1. MAE
2. RMSE
3. Conversion Rate
4. Precision, Recall and F-Measure

References

https://www.kaggle.com/code/saurav9786/recommender-system-using-amazon-reviews/notebook#Analyzing-the-rating

https://towardsdatascience.com/evaluating-a-real-life-recommender-system-error-based-and-ranking-based-84708e3285b

https://github.com/NicolasHug/Surprise/blob/master/examples/top_n_recommendations.py

https://surprise.readthedocs.io/en/latest/FAQ.html#how-to-compute-precision-k-and-recall-k

https://medium.com/human-in-a-machine-world/mae-and-rmse-which-metric-is-better-e60ac3bde13d