DOC add precomputed sparse nearest neighbors graph in release… (#15168)

TomDLT · thomasjpfan · commit 94366b83195b · 2019-10-15T22:14:31.000-04:00
diff --git a/examples/release_highlights/plot_release_highlights_0_22_0.py b/examples/release_highlights/plot_release_highlights_0_22_0.py
@@ -117,3 +117,30 @@
 
 titanic = fetch_openml('titanic', version=1, as_frame=True)
 print(titanic.data.head()[['pclass', 'embarked']])
+
+############################################################################
+# Precomputed sparse nearest neighbors graph
+# ------------------------------------------
+# Most estimators based on nearest neighbors graphs now accept precomputed
+# sparse graphs as input, to reuse the same graph for multiple estimator fits.
+# To use this feature in a pipeline, one can use the `memory` parameter, along
+# with one of the two new transformers,
+# :class:`~sklearn.neighbors.KNeighborsTransformer` and
+# :class:`~sklearn.neighbors.RadiusNeighborsTransformer`. The precomputation
+# can also be performed by custom estimators to use alternative
+# implementations, such as approximate nearest neighbors methods.
+# See more details in the :ref:`User Guide <neighbors_transformer>`.
+
+from sklearn.neighbors import KNeighborsTransformer
+from sklearn.manifold import Isomap
+from sklearn.pipeline import make_pipeline
+
+estimator = make_pipeline(
+    KNeighborsTransformer(n_neighbors=10, mode='distance'),
+    Isomap(n_neighbors=10, metric='precomputed'),
+    memory='.')
+estimator.fit(X)
+
+# We can decrease the number of neighbors and the graph will not be recomputed.
+estimator.set_params(isomap__n_neighbors=5)
+estimator.fit(X)
