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.