8000 DOC Update residual references of class_weight as balanced by krishnakalyan3 · Pull Request #6853 · scikit-learn/scikit-learn · GitHub
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DOC Update residual references of class_weight as balanced #6853

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Merged
merged 3 commits into from
Jun 2, 2016
Merged

DOC Update residual references of class_weight as balanced #6853

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18092fd
fix balance
krishnakalyan3 Jun 2, 2016
0f76f18
fix Indentation and redundant info
krishnakalyan3 Jun 2, 2016
6064327
fix Indentation and redundant info
krishnakalyan3 Jun 2, 2016
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2 changes: 1 addition & 1 deletion doc/modules/grid_search.rst
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Expand Up @@ -101,7 +101,7 @@ For each parameter, either a distribution over possible values or a list of
discrete choices (which will be sampled uniformly) can be specified::

[{'C': scipy.stats.expon(scale=100), 'gamma': scipy.stats.expon(scale=.1),
'kernel': ['rbf'], 'class_weight':['auto', None]}]
'kernel': ['rbf'], 'class_weight':['balanced', None]}]

This example uses the ``scipy.stats`` module, which contains many useful
distributions for sampling parameters, such as ``expon``, ``gamma``,
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8 changes: 4 additions & 4 deletions sklearn/svm/classes.py
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Expand Up @@ -588,12 +588,12 @@ class NuSVC(BaseSVC):
cache_size : float, optional
Specify the size of the kernel cache (in MB).

class_weight : {dict, 'auto'}, optional
class_weight : {dict, 'balanced'}, optional
Set the parameter C of class i to class_weight[i]*C for
SVC. If not given, all classes are supposed to have
weight one. The 'auto' mode uses the values of y to
automatically adjust weights inversely proportional to
class frequencies.
weight one. The "balanced" mode uses the values of y to automatically adjust
weights inversely proportional to class frequencies as
``n_samples / (n_classes * np.bincount(y))``

verbose : bool, default: False
Enable verbose output. Note that this setting takes advantage of a
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