DOC Adjusts OneHotEncoder docstring on multicollinearity
@@ -223,7 +223,7 @@ class OneHotEncoder(_BaseEncoder):
Specifies a methodology to use to drop one of the categories per
feature. This is useful in situations where perfectly collinear
features cause problems, such as when feeding the resulting data
- into a neural network or an unregularized regression.
+ into an unregularized linear regression model.
However, dropping one category breaks the symmetry of the original
representation and can therefore induce a bias in downstream models,
