A Python implementation of LightFM, a hybrid recommendation algorithm.
Apache License 2.0
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ValueError: Test interactions matrix and train interactions matrix share 95786 interactions. This will cause incorrect evaluation, check your data split. #553
I am trying to create a hybrid recommender using item's features
I have a dataset with 478,930 interactions
I am quite sure that each user-item pairs available only once in my data,
so it should be no interactions shared between train and test sets
However, I keep getting the issue:
ValueError: Test interactions matrix and train interactions matrix share 95786 interactions. This will cause incorrect evaluation, check your data split.
How can I solve this?
What are the potential reasons for this?
Hi
I am trying to create a hybrid recommender using item's features I have a dataset with 478,930 interactions I am quite sure that each user-item pairs available only once in my data, so it should be no interactions shared between train and test sets
However, I keep getting the issue: ValueError: Test interactions matrix and train interactions matrix share 95786 interactions. This will cause incorrect evaluation, check your data split.
How can I solve this? What are the potential reasons for this?