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README.rst

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TreeInterpreter
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.. image:: https://img.shields.io/travis/andosa/treeinterpreter.svg
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:target: https://travis-ci.org/andosa/treeinterpreter
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.. image:: https://img.shields.io/pypi/v/treeinterpreter.svg
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:target: https://pypi.python.org/pypi/treeinterpreter
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Package for interpreting scikit-learn's decision tree and random forest predictions.
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Allows decomposing each prediction into bias and feature contribution components as described in http://blog.datadive.net/interpreting-random-forests/. For a dataset with ``n`` features, each prediction on the dataset is decomposed via ``prediction = bias + feature_1_contribution + ... + feature_n_contribution``.
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Allows decomposing each prediction into bias and feature contribution components as described in http://blog.datadive.net/interpreting-random-forests/. For a dataset with ``n`` features, each prediction on the dataset is decomposed as ``prediction = bias + feature_1_contribution + ... + feature_n_contribution``.
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It works on scikit-learn's
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