DOC Document attributes of regressor classes within neighbors submodule.
@@ -89,6 +89,19 @@ class KNeighborsRegressor(NeighborsBase, KNeighborsMixin,
for more details.
Doesn't affect :meth:`fit` method.
+ Attributes
+ ----------
+ effective_metric_ : string or callable
+ The distance metric to use. It will be same as the `metric` parameter
+ or a synonym of it, e.g. 'euclidean' if the `metric` parameter set to
+ 'minkowski' and `p` parameter set to 2.
+
+ effective_metric_params_ : dict
+ Additional keyword arguments for the metric function. For most metrics
+ will be same with `metric_params` parameter, but may also contain the
+ `p` parameter value if the `effective_metric_` attribute is set to
+ 'minkowski'.
+
Examples
--------
>>> X = [[0], [1], [2], [3]]
@@ -246,6 +259,19 @@ class RadiusNeighborsRegressor(NeighborsBase, RadiusNeighborsMixin,
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
+ Attributes
+ ----------
+ effective_metric_ : string or callable
+ The distance metric to use. It will be same as the `metric` parameter
+ or a synonym of it, e.g. 'euclidean' if the `metric` parameter set to
+ 'minkowski' and `p` parameter set to 2.
+
+ effective_metric_params_ : dict
+ Additional keyword arguments for the metric function. For most metrics
+ will be same with `metric_params` parameter, but may also contain the
+ `p` parameter value if the `effective_metric_` attribute is set to
+ 'minkowski'.
+
Examples
--------
>>> X = [[0], [1], [2], [3]]
