feat: invert power transform/scaling order #207
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On main we power transform then standard scale the results, matching sklearn. This PR tries out scaling then power transforming instead.
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I think we should make this flexible, and use an enum indicating if we should standardize before, after, or not at all. |
Allow users to specify if they do not want to scale their data, or to scale it either before or after doing a power transformation. This allows both matching the sklearn behavior of scaling the data after the transformation, or scaling it before the transformation which can help with data that floors at non-zero values.
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If we scale before transforming then some values may become negative and a Box Cox transformation is no longer valid. This commit waits to choose which transformation algorithm to use until after potentially scaling the data.
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Superseded by #213 which makes it easier for callers to standardize before/after power transforming. |
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On
mainwe power transform then standard scale the results, matching sklearn. This PR tries out scaling then power transforming instead.