[MRG +1] DOC - add example to cross_val_predict and cross_val_score #6446
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| >>> X = diabetes.data[:150] | ||
| >>> y = diabetes.target[:150] | ||
| >>> lasso = linear_model.Lasso() | ||
| >>> print(cross_val_predict(lasso, X, y)[:5]) # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS |
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I'd remove the [:5] and use ELLIPSIS
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besides LGTM |
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What is LGTM? I put the :5 otherwise the output would be to long. But I'll change it. You mean only ELLIPSIS? besides LGTM — |
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LGTM =looks good to me. Generally signifies reviewer approval. On Wed, Feb 24, 2016, 1:45 PM Alejandro Correa Bahnsen <
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this looks good to me (after fixing the changes @agramfort suggested) |
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I adjust the output of cross_val_predict to be saved in y_pred (similar as https://github.com/scikit-learn/scikit-learn/blob/51a765a/sklearn/cross_decomposition/pls_.py#L575) |
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LGTM |
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Guys, what is the next step? |
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LGTM. |
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@albahnsen Could you rebase on top of master and resolve the conflicts please ? |
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Guys I'm not sure if I did it correctly. |
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hmm it doesn't seem like you did. you should do the following:
Now, you want to put your changes on top of your local master branch (which is now a copy of scikit-learn's master branch)
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You did it, thanks @albahnsen. |
…cikit-learn#6446) * add example to cross_val_predict and cross_val_score * fix output of cross_val_predict * add example to cross_val_predict and cross_val_score * fix output of cross_val_predict * fix rebase
…cikit-learn#6446) * add example to cross_val_predict and cross_val_score * fix output of cross_val_predict * add example to cross_val_predict and cross_val_score * fix output of cross_val_predict * fix rebase
Add example code to the cross_val_predict and cross_val_score functions.
Simply load diabetes dataset and using a lasso model show how both functions work.