Comments (1)
Your categorical features must have a lot of categories to result in 35k features after binarization.
I recommend that you look at FeatureBinarizerFromTrees (PR #77, thanks to @floidgilbert) and the notebook illustrating its usage. Instead of creating binary features for all possible categories like FeatureBinarizer, it generates them based on splits in fitted decision trees. This should result in a much smaller number of relevant features.
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Related Issues (20)
- Defect FeatureBinarizer HOT 1
- Version reconciliation with AIF360
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