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MNT accelerate plot_gradient_boosting_early_stopping.py example #21609

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Merged
merged 5 commits into from
Nov 27, 2021
Merged

MNT accelerate plot_gradient_boosting_early_stopping.py example #21609

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e006d2a
accelerate plot_gradient_boosting_early_stopping.py example #21598
sply88 Nov 9, 2021
07f35f0
Ran black on changed example
sply88 Nov 10, 2021
b693fa2
digits replaced by make_classification and less samples hastie
sply88 Nov 12, 2021
3b27ad9
Fix random state for plot_gradient_boosting_early_stopping.py
sply88 Nov 27, 2021
c76b48e
Merge branch 'scikit-learn:main' into accelerate-plot_gradient_boosti…
sply88 Nov 27, 2021
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12 changes: 7 additions & 5 deletions examples/ensemble/plot_gradient_boosting_early_stopping.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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 = []
Expand All @@ -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(
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