MNT Update doc and param validation for SequentialFeatureSelector about scoring
@@ -64,13 +64,12 @@ class SequentialFeatureSelector(SelectorMixin, MetaEstimatorMixin, BaseEstimator
direction : {'forward', 'backward'}, default='forward'
Whether to perform forward selection or backward selection.
- scoring : str, callable, list/tuple or dict, default=None
+ scoring : str or callable, default=None
A single str (see :ref:`scoring_parameter`) or a callable
(see :ref:`scoring`) to evaluate the predictions on the test set.
- NOTE that when using custom scorers, each scorer should return a single
- value. Metric functions returning a list/array of values can be wrapped
- into multiple scorers that return one value each.
+ NOTE that when using a custom scorer, it should return a single
+ value.
If None, the estimator's score method is used.
@@ -156,14 +155,7 @@ class SequentialFeatureSelector(SelectorMixin, MetaEstimatorMixin, BaseEstimator
],
"tol": [None, Interval(Real, 0, None, closed="neither")],
"direction": [StrOptions({"forward", "backward"})],
- "scoring": [
- None,
- StrOptions(set(get_scorer_names())),
- callable,
- list,
- dict,
- tuple,
- ],
+ "scoring": [None, StrOptions(set(get_scorer_names())), callable],
"cv": ["cv_object"],
"n_jobs": [None, Integral],
}
