The collaborative filtering toolkit provides tools to identify patterns of user interests and make targeted recommendations.
Most of the algorithms take the rating matrix R, which is a sparse matrix holding the rating given by users to movies, and builds a linear model, finding two low dimensional matrices
U and V s.t. their product approximates R: R ~ UV.
We implement multiple collaborative filtering algorithms: ALS (Alternating least squares), SGD (Stochastic Gradient Descent) , Bias SGD, Weighted-ALS, Sparse-ALS, SVD++. See the Collaborative Filtering Toolkit Documentation for further details.