DOC Clarify threshold param in SelectFromModel (scikit-learn#24039)

neurodata · Jul 29, 2022 · 1074aeb · 1074aeb
1 parent 480ec95
commit 1074aeb
Showing 1 changed file with 3 additions and 3 deletions.
diff --git a/sklearn/feature_selection/_from_model.py b/sklearn/feature_selection/_from_model.py
@@ -97,9 +97,9 @@ class SelectFromModel(MetaEstimatorMixin, SelectorMixin, BaseEstimator):
 
  threshold : str or float, default=None
  The threshold value to use for feature selection. Features whose
- importance is greater or equal are kept while the others are
- discarded. If "median" (resp. "mean"), then the ``threshold`` value is
- the median (resp. the mean) of the feature importances. A scaling
+ absolute importance value is greater or equal are kept while the others
+ are discarded. If "median" (resp. "mean"), then the ``threshold`` value
+ is the median (resp. the mean) of the feature importances. A scaling
  factor (e.g., "1.25*mean") may also be used. If None and if the
  estimator has a parameter penalty set to l1, either explicitly
  or implicitly (e.g, Lasso), the threshold used is 1e-5.