More general predict proba. #6817
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Marked as blocking for 2 reasons.
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python-package/xgboost/sklearn.py
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| # softprob: Do nothing, output is proba. | ||
| # softmax: Use output margin to remove the argmax in PredTransform. | ||
| # binary:logistic: Expand the prob vector into 2-class matrix after predict. | ||
| # binary:logitraw: Unsupported, let's deprecate this objective when possible. |
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I've seen at least a few users using this objective. Should we actually deprecate it?
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It's not clear to me in what scenario is it useful.
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If you want to have an untransformed prediction, use output_margin instead.
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So far we've avoided breaking existing model files, i.e. you could load a very old model file and run predictions. Removing support for binary:logitraw will make old models files inaccessible. We don't yet have a formal policy for changes affecting old model files. (e.g. Wait 3 major versions?)
The objective binary:logitraw is clearly used in the wild already. For example: #6509
* Use `output_margin` for `softmax`. * Add test for dask binary cls.
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Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
* Use `output_margin` for `softmax`. * Add test for dask binary cls. Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
output_marginforsoftmax.