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logistic loss not working? #129

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josepablog opened this issue Dec 5, 2016 · 1 comment

josepablog commented Dec 5, 2016 •

edited

I trained a model lfm with logistic loss.

lfm = lightfm.LightFM(no_components=1, loss="logistic")
lfm.fit(sparse_positive, epochs=100)
lfm.predict(students,  items)

Returns:

array([ 7.49537325,  8.20262432,  7.60994577, ...,  4.16664028,
        5.1302681 ,  3.18788409])

Shouldn't the output be bounded [0..1]?

The text was updated successfully, but these errors were encountered:

Collaborator

maciejkula commented Dec 6, 2016

I think what's happening is that the sigmoid function is simply not applied to the outputs.

Arguably it should be, but I'm hesitant to make this fix as it would change the public API in a way that's not backwards-compatible.

maciejkula closed this as completed

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