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Implement the Yeo-Johnson transform as part of PowerTransformer
See original GitHub issueDescription
Right now, sklearn.preprocessing.PowerTransformer implements the Box-Cox transform (#10210), which only works on positive, nonzero data. The Yeo-Johnson transform is an alternative power transformation that supports negative and zero values. Yeo and Johnson also proposed a more robust technique for selecting the transformation parameter (paper linked below), which may be a good alternative to maximum likelihood.
Original paper Parameter estimation
Comments
@jwilber and I plan to tackle this implementation together.
Issue Analytics
- State:
- Created 6 years ago
- Reactions:7
- Comments:9 (7 by maintainers)
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No big deal, just excited to have something a little bit less constrained than boxcox. It’s harder to make it default behaviour if we’ve already released PowerTransformer, which I suspect we will have before this change is merged.
@jnothman Hey Joel - school just finished so we’ll be able to dedicate time to this for real this time. Sorry for the linger. We’ll submit a PR in 2-3 weeks. cc @chang