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Implementation of hinge loss for binary classification (#3477)

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Henry Gouk
2018-08-07 10:06:42 +12:00
committed by Rory Mitchell
parent 44811f2330
commit 69454d9487
5 changed files with 94 additions and 0 deletions
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doc/parameter.rst
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@@ -248,6 +248,7 @@ Specify the learning task and the corresponding learning objective. The objectiv
- ``reg:logistic``: logistic regression
- ``binary:logistic``: logistic regression for binary classification, output probability
- ``binary:logitraw``: logistic regression for binary classification, output score before logistic transformation
- ``binary:hinge``: hinge loss for binary classification. This makes predictions of 0 or 1, rather than producing probabilities.
- ``gpu:reg:linear``, ``gpu:reg:logistic``, ``gpu:binary:logistic``, ``gpu:binary:logitraw``: versions
of the corresponding objective functions evaluated on the GPU; note that like the GPU histogram algorithm,
they can only be used when the entire training session uses the same dataset