DOC Give local recommendations about SimpleImputer in docstring
@@ -136,7 +136,10 @@ class _BaseImputer(TransformerMixin, BaseEstimator):
class SimpleImputer(_BaseImputer):
- """Imputation transformer for completing missing values.
+ """Univariate imputer for completing missing values with simple strategies.
+
+ Replace missing values using a descriptive statistic (e.g. mean, median, or
+ most frequent) along each column, or using a constant value.
Read more in the :ref:`User Guide <impute>`.
@@ -224,13 +227,21 @@ class SimpleImputer(_BaseImputer):
See Also
--------
- IterativeImputer : Multivariate imputation of missing values.
+ IterativeImputer : Multivariate imputer that estimates values to impute for
+ each feature with missing values from all the others.
+ KNNImputer : Multivariate imputer that estimates missing features using
+ nearest samples.
Notes
-----
Columns which only contained missing values at :meth:`fit` are discarded
upon :meth:`transform` if strategy is not `"constant"`.
+ In a prediction context, simple imputation usually performs poorly when
+ associated with a weak learner. However, with a powerful learner, it can
+ lead to as good or better performance than complex imputation such as
+ :class:`~sklearn.impute.IterativeImputer` or :class:`~sklearn.impute.KNNImputer`.
+
Examples
--------
>>> import numpy as np
