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5 | 5 |
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6 | 6 | from sklearn.utils.testing import assert_almost_equal, assert_array_equal
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7 | 7 | from sklearn.utils.testing import assert_array_almost_equal
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8 |
| -from sklearn.utils.testing import assert_equal, assert_true, assert_false |
| 8 | +from sklearn.utils.testing import assert_equal |
9 | 9 | from sklearn.utils.testing import assert_raise_message
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10 | 10 | from sklearn.exceptions import NotFittedError
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11 | 11 | from sklearn.linear_model import LogisticRegression
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@@ -337,7 +337,7 @@ def test_set_params():
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337 | 337 | eclf2 = VotingClassifier([('lr', clf1), ('nb', clf3)], voting='soft',
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338 | 338 | weights=[1, 2])
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339 | 339 | eclf2.set_params(nb=clf2).fit(X, y)
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340 |
| - assert_false(hasattr(eclf2, 'nb')) |
| 340 | + assert not hasattr(eclf2, 'nb') |
341 | 341 |
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342 | 342 | assert_array_equal(eclf1.predict(X), eclf2.predict(X))
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343 | 343 | assert_array_almost_equal(eclf1.predict_proba(X), eclf2.predict_proba(X))
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@@ -374,8 +374,8 @@ def test_set_estimator_none():
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374 | 374 |
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375 | 375 | assert dict(eclf2.estimators)["rf"] is None
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376 | 376 | assert len(eclf2.estimators_) == 2
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377 |
| - assert_true(all([not isinstance(est, RandomForestClassifier) for est in |
378 |
| - eclf2.estimators_])) |
| 377 | + assert all(isinstance(est, (LogisticRegression, GaussianNB)) |
| 378 | + for est in eclf2.estimators_) |
379 | 379 | assert eclf2.get_params()["rf"] is None
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380 | 380 |
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381 | 381 | eclf1.set_params(voting='soft').fit(X, y)
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