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"Label" for One-Class Matrix Factorization

 3 years ago
source link: https://github.com/dotnet/machinelearning-samples/issues/873
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sergey-tihon commented yesterday •

edited

There is a sample in this project MatrixFactorization_ProductRecommendation for "One-Class Matrix Factorization"

In this sample traindata loaded from 2 column file and added one more Label column in the dataset
https://github.com/dotnet/machinelearning-samples/blob/master/samples/csharp/getting-started/MatrixFactorization_ProductRecommendation/ProductRecommender/Program.cs#L31-L39

var traindata = mlContext.Data.LoadFromTextFile(path:TrainingDataLocation,
                                                      columns: new[]
                                                                {
                                                                    new TextLoader.Column("Label", DataKind.Single, 0), // HERE
                                                                    new TextLoader.Column(name:nameof(ProductEntry.ProductID), dataKind:DataKind.UInt32, source: new [] { new TextLoader.Range(0) }, keyCount: new KeyCount(262111)), 
                                                                    new TextLoader.Column(name:nameof(ProductEntry.CoPurchaseProductID), dataKind:DataKind.UInt32, source: new [] { new TextLoader.Range(1) }, keyCount: new KeyCount(262111))
                                                                },
                                                      hasHeader: true,
                                                      separatorChar: '\t');

when column added it is filled with NaNs

According to documentation for MatrixFactorizationTrainer Class

The coordinate descent method included is specifically for one-class matrix factorization where all observed ratings are positive signals (that is, all rating values are 1). Notice that the only way to invoke one-class matrix factorization is to assign one-class squared loss to loss function when calling MatrixFactorization(Options). See Page 6 and Page 28 here for a brief introduction to standard matrix factorization and one-class matrix factorization.

Page 28 of linked paper also state that

'One-Class Matrix Factorization' method is used when we know only positive ratings/samples (1s)

Why MatrixFactorization_ProductRecommendation sample does not fill Label column with all 1s before matrix factorization?

// cc @CESARDELATORRE

Update: Here is more detailed explanation


report

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