DOC Accelerate plot_missing_values.py example (#21792)

hansinahuja · adrinjalali · glemaitre · glemaitre · commit 829d9c6cf41d · 2022-05-19T14:13:33.000+02:00
Co-authored-by: Adrin Jalali &lt;adrin.jalali@gmail.com&gt;
Co-authored-by: Guillaume Lemaitre &lt;g.lemaitre58@gmail.com&gt;
diff --git a/examples/impute/plot_missing_values.py b/examples/impute/plot_missing_values.py
@@ -52,8 +52,10 @@
 
 X_diabetes, y_diabetes = load_diabetes(return_X_y=True)
 X_california, y_california = fetch_california_housing(return_X_y=True)
-X_california = X_california[:400]
-y_california = y_california[:400]
+X_california = X_california[:300]
+y_california = y_california[:300]
+X_diabetes = X_diabetes[:300]
+y_diabetes = y_diabetes[:300]
 
 
 def add_missing_values(X_full, y_full):
@@ -98,7 +100,7 @@ def add_missing_values(X_full, y_full):
 from sklearn.pipeline import make_pipeline
 
 
-N_SPLITS = 5
+N_SPLITS = 4
 regressor = RandomForestRegressor(random_state=0)
 
 # %%
@@ -231,7 +233,8 @@ def get_impute_iterative(X_missing, y_missing):
         missing_values=np.nan,
         add_indicator=True,
         random_state=0,
-        n_nearest_features=5,
+        n_nearest_features=3,
+        max_iter=1,
         sample_posterior=True,
     )
     iterative_impute_scores = get_scores_for_imputer(imputer, X_missing, y_missing)
