[MRG+2] ENH/MNT results_ --> cv_results; test_mean_score --> mean_test_score et al.#7324
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doc/whats_new.rst
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| :class:`model_selection.RandomizedSearchCV` utilities. | ||
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| - **The enhanced `results_` attribute** | ||
| - **The enhanced `cv_results_` attribute** |
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What about examples? You should be able to get no results from |
Oops! Good catch! I think that's why circle is failing... |
sklearn/model_selection/_search.py
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| self.cv_results_['params'], | ||
| self.cv_results_['mean_test_score'], | ||
| self.cv_results_['std_test_score'])): | ||
| scores = np.array(list(self.cv_results_['split%d_test_score' % |
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maybe move % to the next line?
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You didn't actually run that git grep, did you? |
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Once you've got those last two, the file list covers #6697. |
| 'test_mean_score' : [0.81, 0.60, 0.75, 0.82], | ||
| 'test_std_score' : [0.02, 0.01, 0.03, 0.03], | ||
| 'test_rank_score' : [2, 4, 3, 1], | ||
| 'split0_test_score' : [0.8, 0.7, 0.8, 0.9], |
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Confirming with @amueller: these names work better for you?
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And after those tutorial examples, this LGTM. |
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why cosmit? |
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Thanks for the review and +1 :) |
😛 |
| for i in range(len(clf.results_['params'])): | ||
| means = clf.cv_results_['mean_test_score'] | ||
| stds = clf.cv_results_['std_test_score'] | ||
| for mean, std, params in zip(means, stds, clf.cv_results_['params']): |
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I used this chance to address an old review ;)
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Why did travis not run on this? other than that: LGTM. And changing the book again lol |
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haha |
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I'll try a rebase-force-push and see if that restarts travis... |
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Thanks! |
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Thanks for the reviews and merge! |
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Thank you for doing all the messy work! On 8 September 2016 at 05:53, Raghav RV notifications@github.com wrote:
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Addresses #7205
@amueller @jnothman