prediction_algorithms packageΒΆ

The prediction_algorithms package includes the prediction algorithms available for recommendation.

The available prediction algorithms are:

random_pred.NormalPredictor

Algorithm predicting a random rating based on the distribution of the training set, which is assumed to be normal.

baseline_only.BaselineOnly

Algorithm predicting the baseline estimate for given user and item.

knns.KNNBasic

A basic collaborative filtering algorithm.

knns.KNNWithMeans

A basic collaborative filtering algorithm, taking into account the mean ratings of each user.

knns.KNNWithZScore

A basic collaborative filtering algorithm, taking into account the z-score normalization of each user.

knns.KNNBaseline

A basic collaborative filtering algorithm taking into account a baseline rating.

matrix_factorization.SVD

The famous SVD algorithm, as popularized by Simon Funk during the Netflix Prize.

matrix_factorization.SVDpp

The SVD++ algorithm, an extension of SVD taking into account implicit ratings.

matrix_factorization.NMF

A collaborative filtering algorithm based on Non-negative Matrix Factorization.

slope_one.SlopeOne

A simple yet accurate collaborative filtering algorithm.

co_clustering.CoClustering

A collaborative filtering algorithm based on co-clustering.

You may want to check the notation standards before diving into the formulas.