8000 DOC: document negative weight treatment in the case of classification by ndawe · Pull Request #8 · glouppe/scikit-learn · GitHub
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DOC: document negative weight treatment in the case of classification #8

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Jan 6, 2013
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DOC: document negative weight treatment in the case of classification #8

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6 changes: 4 additions & 2 deletions sklearn/tree/tree.py
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Expand Up @@ -210,8 +210,10 @@ def fit(self, X, y,

sample_weight : array-like, shape = [n_samples] or None
Sample weights. If None, then samples are equally weighted.
Splits that would yield nodes with net zero or negative weight are
ignored while searching for a split in each node.
Splits that would create child nodes with net zero or negative
weight are ignored while searching for a split in each node. In the
case of classification, splits are also ignored that would result
in any single class carrying a negative weight in either child node.

check_input: boolean, (default=True)
Allow to bypass several input checking.
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