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[WIP] nocats CI testing#7068

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jblackburne wants to merge 35 commits intoscikit-learn:masterscikit-learn/scikit-learn:masterfrom

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Commits on Mar 22, 2016

• Created SplitValue datatype to generalize the concept of a threshold to categorical variables. Replaced the threshold attribute of SplitRecord and Node with SplitValue.

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• Added attribute n_categories to Splitter and Tree, an array of ints that defaults to -1 for each feature (indicating non-categorical feature).

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• Added a goes_left function for evaluating splits.

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• Tree.apply() now uses the goes_left function.

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• Added categorical split code to BestSplitter.node_split

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• Added categorical split code to RandomSplitter.node_split

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• Added a 'categorical' parameter to BaseDecisionTree.fit(). It currently does nothing.

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• Added a property getter/setter for Tree.n_categories

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• Added n_categories arguments to Splitter.init() and TreeBuilder.build(). Enforced max n_categories=2**31 for RandomSplitter.

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• Added python interface for categorical features.

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• Adjusted _gradient_boosting.pyx to match the new splitting mechanism.

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• Added interface code to forest.py and gradient_boosting.py for categorical features.

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• Added bit caches to Splitter and Tree. These are used to avoid regenerating a big list of random numbers for every sample in every node when sending it left or right.

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• Added a check on the predict() and predict_proba() methods of trees that there are no sparse categorical variables, since they're currently not supported.

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• Added property getter for a Tree's split_values in addition to thresholds.

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• Added a check to prevent use of DecisionTree (instead of ExtraTree) with more than 64 categories.

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• Fixed the numpy NODE dtype so it matches the cython struct.

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• Put the gradient boosting tree descent code into a try..finally block to make sure we free the bit cache.

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• Fixed a python3 compatibility problem.

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• Fixed a Splitter validation bug in tree.py

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• RandomSplitter now flips a coin to send each category value left or right

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• For categorical features, RandomSplitter now retries up to 20 random splits until a non-trivial one is found

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• Fixed a nasty bug where categorical normalization was happening incorrectly with ensembles. Refactored the categorical transformations into functions.

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• Added some unit tests. More to come.

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• Upped the maximum number of times RandomSplitter will retry if it accidentally creates a trivial split.

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Commits on Mar 28, 2016

• Added code to BestSplitter to restrict split trials to categories represented in the local sample.

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Commits on May 30, 2016

• Fixed a warning, which was actually a compile error in clang.

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• Fixed a bug where BestSplitter was miscalculating impurities for categorical features.

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Commits on May 31, 2016

• Added an implementation of the Breiman shortcut. Turned off for now.

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• Added code to automatically trigger the Breiman shortcut when appropriate for categorical features.

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Commits on Jun 5, 2016

• Fixed a left-shift-too-far (undefined behavior) bug.

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Commits on Jul 9, 2016

• Removed numpy access to the split value union to pacify unit tests run with numpy v1.6. This should be reverted when support for numpy v1.6 is dropped.

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Commits on Jul 14, 2016

• Replaced a call to np.full with np.ones, to accomodate older versions of numpy.

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• Moved the categorical parameter from fit() to the constructor, for trees, forests, and gradient boosting. Tweaked unit tests to match.

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Commits on Jul 23, 2016

• Added printf debug statements.

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