MNT accelerate plot_gradient_boosting_early_stopping.py example (scikit-learn#21609)

sply88 · thomasjpfan · web-flow · commit 832513a7fb65 · 2021-11-27T18:51:02.000-05:00
Co-authored-by: Thomas J. Fan &lt;thomasjpfan@gmail.com&gt;
diff --git a/examples/ensemble/plot_gradient_boosting_early_stopping.py b/examples/ensemble/plot_gradient_boosting_early_stopping.py
@@ -45,10 +45,12 @@
 from sklearn import datasets
 from sklearn.model_selection import train_test_split
 
-data_list = [datasets.load_iris(), datasets.load_digits()]
-data_list = [(d.data, d.target) for d in data_list]
-data_list += [datasets.make_hastie_10_2()]
-names = ["Iris Data", "Digits Data", "Hastie Data"]
+data_list = [
+    datasets.load_iris(return_X_y=True),
+    datasets.make_classification(n_samples=800, random_state=0),
+    datasets.make_hastie_10_2(n_samples=2000, random_state=0),
+]
+names = ["Iris Data", "Classification Data", "Hastie Data"]
 
 n_gb = []
 score_gb = []
@@ -57,7 +59,7 @@
 score_gbes = []
 time_gbes = []
 
-n_estimators = 500
+n_estimators = 200
 
 for X, y in data_list:
     X_train, X_test, y_train, y_test = train_test_split(
