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Surprise

Suprise-Python Wrapper for Persa.jl

Readme

Surprise.jl - Wrapper to Surprise Python Package

Build Status Coverage Status codecov.io

Installation: at the Julia REPL, Pkg.add("Surprise")

Reporting Issues and Contributing: See CONTRIBUTING.md

Goal

The main aim is to create a framework that facilitates the study of recommender systems in Julia.

Example

julia> using Persa

julia> using DatasetsCF

julia> using Surprise

julia> dataset = DatasetsCF.MovieLens();

julia> (ds_train, ds_test) = Persa.get(Persa.HoldOut(dataset, 0.9));

julia> model = Surprise.IRSVD(ds_train);

julia> Persa.train!(model, ds_train)

julia> print(Persa.aval(model, ds_test))
MAE - 0.7380270708513149
RMSE - 0.9369961685890544
Coverage - 0.9988001199880012

Algorithms

List of collaborative algorithms:

Algorithm Description
KNNBasic A basic KNN algorithm.
KNNBaseline A basic KNN algorithm but using a baseline factor.
KNNWithMeans A basic KNN algorithm but using user or item mean.
SlopeOne SlopeOne algorithm.
RSVD Regulared SVD. The algorithm is also known as SVD by Funk.
IRSVD Improved Regulared SVD. Extension of RSVD algorithm adding the user and item bias.

First Commit

04/18/2017

Last Touched

over 1 year ago

Commits

32 commits

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