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[MRG + 1] Fixed impossible min_samples_split value #9520

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Aug 11, 2017
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[MRG + 1] Fixed impossible min_samples_split value #9520

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2 changes: 1 addition & 1 deletion doc/modules/ensemble.rst
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Expand Up @@ -202,7 +202,7 @@ bias. Empirical good default values are ``max_features=n_features``
for regression problems, and ``max_features=sqrt(n_features)`` for
classification tasks (where ``n_features`` is the number of features
in the data). Good results are often achieved when setting ``max_depth=None``
in combination with ``min_samples_split=1`` (i.e., when fully developing the
in combination with ``min_samples_split=2`` (i.e., when fully developing the
trees). Bear in mind though that these values are usually not optimal, and
might result in models that consume a lot of RAM. The best parameter values
should always be cross-validated. In addition, note that in random forests,
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