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DOC Fix FutureWarning in ensemble/plot_gradient_boosting_regularization.html #24960

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Merged
merged 3 commits into from
Nov 21, 2022
Merged

DOC Fix FutureWarning in ensemble/plot_gradient_boosting_regularization.html #24960

merged 3 commits into from
Nov 21, 2022

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Reddragonemperor58
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Reference Issues/PRs
Related to #24876

What does this implement/fix? Explain your changes.

Fix FutureWarning in ensemble/plot_gradient_boosting_regularization.html

/home/runner/work/scikit-learn/scikit-learn/sklearn/utils/deprecation.py:101: FutureWarning:

Attribute `loss_` was deprecated in version 1.1 and will be removed in 1.3.

/home/runner/work/scikit-learn/scikit-learn/sklearn/utils/deprecation.py:101: FutureWarning:

Attribute `loss_` was deprecated in version 1.1 and will be removed in 1.3.

/home/runner/work/scikit-learn/scikit-learn/sklearn/utils/deprecation.py:101: FutureWarning:

Attribute `loss_` was deprecated in version 1.1 and will be removed in 1.3.

/home/runner/work/scikit-learn/scikit-learn/sklearn/utils/deprecation.py:101: FutureWarning:

Attribute `loss_` was deprecated in version 1.1 and will be removed in 1.3.

/home/runner/work/scikit-learn/scikit-learn/sklearn/utils/deprecation.py:101: FutureWarning:

Attribute `loss_` was deprecated in version 1.1 and will be removed in 1.3.

Any other comments?

glemaitre
glemaitre reviewed Nov 16, 2022
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examples/ensemble/plot_gradient_boosting_regularization.py Outdated
@@ -76,7 +79,7 @@

for i, y_pred in enumerate(clf.staged_decision_function(X_test)):
# clf.loss_ assumes that y_test[i] in {0, 1}
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Remove this line

examples/ensemble/plot_gradient_boosting_regularization.py Outdated
@@ -76,7 +79,7 @@

for i, y_pred in enumerate(clf.staged_decision_function(X_test)):
# clf.loss_ assumes that y_test[i] in {0, 1}
test_deviance[i] = clf.loss_(y_test, y_pred)
test_deviance[i] = binomial_deviance(y_test, y_pred.ravel())
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@glemaitre glemaitre Nov 16, 2022 •
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Actually we can use staged_predict_proba directly:

    for i, y_proba in enumerate(clf.staged_predict_proba(X_test)):
        test_deviance[i] = 2 * log_loss(y_test, y_proba[:, 1])

examples/ensemble/plot_gradient_boosting_regularization.py Outdated
Comment on lines 51 to 53
def binomial_deviance(y, raw_predictions):
return -2 * np.mean((y * raw_predictions) - np.logaddexp(0, raw_predictions))

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You can remove this function and we will use the log_loss.

examples/ensemble/plot_gradient_boosting_regularization.py Outdated
@@ -48,6 +48,9 @@
"min_samples_split": 5,
}

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Please import the log loss after line 34:

from sklearn.metrics import log_loss

examples/ensemble/plot_gradient_boosting_regularization.py Outdated
@@ -91,3 +94,4 @@
plt.ylabel("Test Set Deviance")

plt.show()

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Not really sure that we need this additional line.

@glemaitre glemaitre mentioned this pull request Nov 17, 2022
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@Reddragonemperor58 Reddragonemperor58 mentioned this pull request Nov 17, 2022
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@glemaitre glemaitre self-requested a review November 21, 2022 09:27
glemaitre
glemaitre approved these changes Nov 21, 2022
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I pushed the small fix

betatim
betatim approved these changes Nov 21, 2022
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This PR feels like dejavu. LGTM though

@glemaitre
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This PR feels like dejavu. LGTM though

Indeed.

@glemaitre glemaitre merged commit 75db1bc into scikit-learn:main Nov 21, 2022
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Thanks @Reddragonemperor58

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@betatim betatim betatim approved these changes

@glemaitre glemaitre glemaitre approved these changes

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@Reddragonemperor58 @glemaitre @betatim