[MRG+1] FIX/DOC Improve documentation regarding non-determinitic tree behaviour#8452
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raghavrv merged 2 commits intoscikit-learn:masterfrom Feb 26, 2017
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[MRG+1] FIX/DOC Improve documentation regarding non-determinitic tree behaviour#8452raghavrv merged 2 commits intoscikit-learn:masterfrom
raghavrv merged 2 commits intoscikit-learn:masterfrom
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This is good. We should also update the website soon as that is the most visible documentation. You edited RandomForestClassifier and RandomForestRegressor as well, yes? |
Codecov Report
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Coverage 95.47% 95.47%
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Files 342 342
Lines 60907 60907
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Hits 58154 58154
Misses 2753 2753
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+1 for MRG |
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@jmschrei Yes I did the change for the random forest, ijust forgot to add it in the first post |
jnothman
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Feb 26, 2017
sklearn/ensemble/forest.py
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| ----- | ||
| The features are always randomly permuted at each split. Therefore, | ||
| the best found split may vary, even with the same training data, | ||
| ``max_feature=n_features`` and ``bootstrap=False``, if the improvement |
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Thx @glemaitre :) |
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… behaviour (scikit-learn#8452) * FIX/DOC Improve documentation regarding non-determinitic tree behaviour * FIX correct max_features
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Reference Issue
Fixes #8443
What does this implement/fix? Explain your changes.
Add details regarding the non-deterministic behaviour of decision tree.
Any other comments?
Edited:
DecisionTreeClassifierDecisionTreeRegressorGradientBoostingClassifierGradientBoostingRegressorRandomForestRegressorRandomForestClassifier