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[breaking] Remove label encoder deprecated in 1.3. (#7357)

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This commit is contained in:
Jiaming Yuan
2021-10-28 13:24:29 +08:00
committed by GitHub
parent d05754f558
commit 3c4aa9b2ea
7 changed files with 74 additions and 83 deletions
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18
tests/python/test_with_sklearn.py
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@@ -283,7 +283,6 @@ def test_feature_importances_gain():
random_state=0, tree_method="exact",
learning_rate=0.1,
importance_type="gain",
use_label_encoder=False,
).fit(X, y)
exp = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
@@ -306,7 +305,6 @@ def test_feature_importances_gain():
tree_method="exact",
learning_rate=0.1,
importance_type="gain",
use_label_encoder=False,
).fit(X, y)
np.testing.assert_almost_equal(xgb_model.feature_importances_, exp)
@@ -315,14 +313,11 @@ def test_feature_importances_gain():
tree_method="exact",
learning_rate=0.1,
importance_type="gain",
use_label_encoder=False,
).fit(X, y)
np.testing.assert_almost_equal(xgb_model.feature_importances_, exp)
# no split can be found
cls = xgb.XGBClassifier(
min_child_weight=1000, tree_method="hist", n_estimators=1, use_label_encoder=False
)
cls = xgb.XGBClassifier(min_child_weight=1000, tree_method="hist", n_estimators=1)
cls.fit(X, y)
assert np.all(cls.feature_importances_ == 0)
@@ -497,7 +492,7 @@ def test_classification_with_custom_objective():
X, y
)
cls = xgb.XGBClassifier(use_label_encoder=False, n_estimators=1)
cls = xgb.XGBClassifier(n_estimators=1)
cls.fit(X, y)
is_called = [False]
@@ -923,7 +918,7 @@ def test_RFECV():
bst = xgb.XGBClassifier(booster='gblinear', learning_rate=0.1,
n_estimators=10,
objective='binary:logistic',
random_state=0, verbosity=0, use_label_encoder=False)
random_state=0, verbosity=0)
rfecv = RFECV(estimator=bst, step=1, cv=3, scoring='roc_auc')
rfecv.fit(X, y)
@@ -934,7 +929,7 @@ def test_RFECV():
n_estimators=10,
objective='multi:softprob',
random_state=0, reg_alpha=0.001, reg_lambda=0.01,
scale_pos_weight=0.5, verbosity=0, use_label_encoder=False)
scale_pos_weight=0.5, verbosity=0)
rfecv = RFECV(estimator=bst, step=1, cv=3, scoring='neg_log_loss')
rfecv.fit(X, y)
@@ -943,7 +938,7 @@ def test_RFECV():
rfecv = RFECV(estimator=reg)
rfecv.fit(X, y)
cls = xgb.XGBClassifier(use_label_encoder=False)
cls = xgb.XGBClassifier()
rfecv = RFECV(estimator=cls, step=1, cv=3,
scoring='neg_mean_squared_error')
rfecv.fit(X, y)
@@ -1052,8 +1047,9 @@ def test_deprecate_position_arg():
with pytest.warns(FutureWarning):
model.fit(X, y, w)
with pytest.warns(FutureWarning):
with pytest.raises(ValueError):
xgb.XGBRFClassifier(1, use_label_encoder=True)
model = xgb.XGBRFClassifier(n_estimators=1)
with pytest.warns(FutureWarning):
model.fit(X, y, w)