ENH accelerate plot_randomized_search.py (#21637)

sply88 · web-flow · commit d7ddffe9c177 · 2021-11-16T09:44:40.000-08:00
diff --git a/examples/model_selection/plot_randomized_search.py b/examples/model_selection/plot_randomized_search.py
@@ -31,7 +31,7 @@
 from sklearn.linear_model import SGDClassifier
 
 # get some data
-X, y = load_digits(return_X_y=True)
+X, y = load_digits(return_X_y=True, n_class=3)
 
 # build a classifier
 clf = SGDClassifier(loss="hinge", penalty="elasticnet", fit_intercept=True)
@@ -57,11 +57,11 @@ def report(results, n_top=3):
 param_dist = {
     "average": [True, False],
     "l1_ratio": stats.uniform(0, 1),
-    "alpha": loguniform(1e-4, 1e0),
+    "alpha": loguniform(1e-2, 1e0),
 }
 
 # run randomized search
-n_iter_search = 20
+n_iter_search = 15
 random_search = RandomizedSearchCV(
     clf, param_distributions=param_dist, n_iter=n_iter_search
 )
@@ -78,7 +78,7 @@ def report(results, n_top=3):
 param_grid = {
     "average": [True, False],
     "l1_ratio": np.linspace(0, 1, num=10),
-    "alpha": np.power(10, np.arange(-4, 1, dtype=float)),
+    "alpha": np.power(10, np.arange(-2, 1, dtype=float)),
 }
 
 # run grid search
