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I noticed a strange issue using the library with the sparse matrices format.
If I use the same interaction matrix but as CSR while training, I get different results when evaluating compared to using a COO matrix for interactions.
Is it a normal behavior ?
Also how can I be certain of the format I should use for all LighFM input:
lightfm.Dataset returns all COO matrices when building interactions and features, but in the source it's said that user_features and item_features should be as CSR.
Thanks for you help !
The text was updated successfully, but these errors were encountered:
I tried both csr and coo matrix on train/test data, and I got nearly the same result(mAP) of model.
But I'm curious about which data format is better for training lightFM model, too.
I noticed a strange issue using the library with the sparse matrices format.
If I use the same interaction matrix but as CSR while training, I get different results when evaluating compared to using a COO matrix for interactions.
Is it a normal behavior ?
Also how can I be certain of the format I should use for all LighFM input:
lightfm.Dataset returns all COO matrices when building interactions and features, but in the source it's said that user_features and item_features should be as CSR.
Thanks for you help !
The text was updated successfully, but these errors were encountered: