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DOC update readme and overview with new features
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kmike committed Jun 2, 2017
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4 changes: 2 additions & 2 deletions README.rst
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Expand Up @@ -36,8 +36,8 @@ It provides support for the following machine learning frameworks and packages:
It also allows to debug scikit-learn pipelines which contain
HashingVectorizer, by undoing hashing.

* xgboost_ - show feature importances and explain predictions of XGBClassifier
and XGBRegressor.
* xgboost_ - show feature importances and explain predictions of XGBClassifier,
XGBRegressor and xgboost.Booster.

* LightGBM_ - show feature importances and explain predictions of
LGBMClassifier and LGBMRegressor.
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4 changes: 3 additions & 1 deletion docs/source/overview.rst
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Expand Up @@ -21,12 +21,14 @@ following machine learning frameworks and packages:
print decision trees as text or as SVG, show feature importances
and explain predictions of decision trees and tree-based ensembles.

Pipeline and FeatureUnion are supported.

ELI5 understands text processing utilities from scikit-learn and can
highlight text data accordingly. It also allows to debug scikit-learn
pipelines which contain HashingVectorizer, by undoing hashing.

* :ref:`library-xgboost` - show feature importances and explain predictions
of XGBClassifier and XGBRegressor.
of XGBClassifier, XGBRegressor and xgboost.Booster.

* :ref:`library-lightgbm` - show feature importances and explain predictions
of LGBMClassifier and LGBMRegressor.
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