[WIP] minimize validation of X in adaboost #8304
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jnothman
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Feb 6, 2017
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This still requires that X be converted to an ndarray (not pandas), that it is finite, and selects sparse types whose preference should be determined by the base estimator, etc. I don't think X needs any validation. Does y? Read the code, work it out. This will depend on the ensemble technique.
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This does beg the question: should we be trying to implement this change,
or close as a WONTFIX. No strong opinion.
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i think our ensemble code, as with other metaestimators, should be robust
to using external estimators as much as possible. But that means creating
mock estimators in tests which check that X is passed unaltered.
…On 8 Feb 2017 5:53 am, "Gael Varoquaux" ***@***.***> wrote:
This does beg the question: should we be trying to implement this change,
or close as a WONTFIX. No strong opinion.
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fixed in #13174. |
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Reference Issue
Fixes #7768
What does this implement/fix? Explain your changes.
This removes the restriction on X to be 2D and transfers the duty of validation of X to the base estimator.
Any other comments?
This has been implemented for only
AdaboostClassifiertill now. If this seems fine, will extend it to other ensembles. Also, docstring hasn't been updated yet.