FEA add ValidationCurveDisplay in model_selection module - #25120
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ping @ArturoAmorQ since this is something that we probably used in the MOOC. |
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Don't forget to add the |
ArturoAmorQ
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Thanks for the PR @glemaitre, this will certainly be a nice addition!
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| >>> from sklearn.model_selection import validation_curve | ||
| >>> from sklearn.datasets import load_iris | ||
| >>> from sklearn.linear_model import Ridge | ||
| >>> from sklearn.svm import SVC |
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The problem here is that we used a regressor for a classification problem.
Co-authored-by: Jérémie du Boisberranger <[email protected]>
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This is a parameter of |
ogrisel
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Another pass. Otherwise LGTM.
Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]>
Co-authored-by: Olivier Grisel <[email protected]>
Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]>
Co-authored-by: Jérémie du Boisberranger <[email protected]>
Fine doing this in another PR. We also need to improve the |
| train and test curves to be consistent with | ||
| :class:`model_selection.ValidationCurveDisplay`. You can set `score_type="test"` to |
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The motivation is more that it's a better default behavior for the typical use cases, rather than consistency
ogrisel
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Once the above suggestions and the following are addressed, LGTM!
Co-authored-by: Olivier Grisel <[email protected]>
Co-authored-by: Olivier Grisel <[email protected]>
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Thanks @glemaitre and @jeremiedbb! |
…n#25120) Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: Olivier Grisel <[email protected]>
Add
ValidationCurveDisplayto themodel_selectionmodule.This is the missing curve for the module.