8000 TST: fix tests on numpy 1.9.b2 · scikit-learn/scikit-learn@41d02e0 · GitHub
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GaelVaroquauxogrisel
GaelVaroquaux
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ogrisel
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TST: fix tests on numpy 1.9.b2
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‎sklearn/metrics/tests/test_ranking.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -867,14 +867,14 @@ def check_alternative_lrap_implementation(lrap_score, n_classes=5,
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y_score = y_score.toarray()
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score_lrap = label_ranking_average_precision_score(y_true, y_score)
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score_my_lrap = _my_lrap(y_true, y_score)
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assert_equal(score_lrap, score_my_lrap)
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assert_almost_equal(score_lrap, score_my_lrap)
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# Uniform score
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random_state = check_random_state(random_state)
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y_score = random_state.uniform(size=(n_samples, n_classes))
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score_lrap = label_ranking_average_precision_score(y_true, y_score)
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score_my_lrap = _my_lrap(y_true, y_score)
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assert_equal(score_lrap, score_my_lrap)
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assert_almost_equal(score_lrap, score_my_lrap)
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def test_label_ranking_avp():

‎sklearn/metrics/tests/test_score_objects.py

Lines changed: 6 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -7,7 +7,6 @@
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from sklearn.utils.testing import assert_raises_regexp
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from sklearn.utils.testing import assert_true
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from sklearn.utils.testing import ignore_warnings
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from sklearn.utils.testing import assert_equal
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from sklearn.utils.testing import assert_not_equal
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from sklearn.metrics import (f1_score, r2_score, roc_auc_score, fbeta_score,
@@ -270,13 +269,12 @@ def test_scorer_sample_weight():
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ignored = scorer(estimator[name], X_test[10:], y_test[10:])
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unweighted = scorer(estimator[name], X_test, y_test)
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assert_not_equal(weighted, unweighted,
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"scorer {0} behaves identically when called with "
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"sample weights: {1} vs {2}".format(name,
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weighted,
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unweighted))
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assert_equal(weighted, ignored,
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"scorer {0} behaves differently when ignoring "
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"samples and setting sample_weight to 0: "
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msg="scorer {0} behaves identically when "
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"called with sample weights: {1} vs "
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"{2}".format(name, weighted, unweighted))
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assert_almost_equal(weighted, ignored,
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err_msg="scorer {0} behaves differently when "
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"ignoring samples and setting sample_weight to 0: "
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"{1} vs {2}".format(name, weighted, ignored))
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except TypeError as e:

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