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[MRG+2] Raise ValueError for metrics.cluster.supervised with too many classes #5445
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Original file line number | Diff line number | Diff line change |
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@@ -181,10 +181,14 @@ def test_exactly_zero_info_score(): | |
for i in np.logspace(1, 4, 4).astype(np.int): | ||
labels_a, labels_b = np.ones(i, dtype=np.int),\ | ||
np.arange(i, dtype=np.int) | ||
assert_equal(normalized_mutual_info_score(labels_a, labels_b), 0.0) | ||
assert_equal(v_measure_score(labels_a, labels_b), 0.0) | ||
assert_equal(adjusted_mutual_info_score(labels_a, labels_b), 0.0) | ||
assert_equal(normalized_mutual_info_score(labels_a, labels_b), 0.0) | ||
assert_equal(normalized_mutual_info_score(labels_a, labels_b, | ||
max_n_classes=1e4), 0.0) | ||
assert_equal(v_measure_score(labels_a, labels_b, | ||
max_n_classes=1e4), 0.0) | ||
assert_equal(adjusted_mutual_info_score(labels_a, labels_b, | ||
max_n_classes=1e4), 0.0) | ||
assert_equal(normalized_mutual_info_score(labels_a, labels_b, | ||
max_n_classes=1e4), 0.0) | ||
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def test_v_measure_and_mutual_information(seed=36): | ||
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@@ -196,3 +200,26 @@ def test_v_measure_and_mutual_information(seed=36): | |
assert_almost_equal(v_measure_score(labels_a, labels_b), | ||
2.0 * mutual_info_score(labels_a, labels_b) / | ||
(entropy(labels_a) + entropy(labels_b)), 0) | ||
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def test_max_n_classes(): | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. You need to create a local random number generator: rng = np.random.RandomState(seed=0) and use it after: labels_true = rng.random(53) |
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rng = np.random.RandomState(seed=0) | ||
labels_true = rng.rand(53) | ||
labels_pred = rng.rand(53) | ||
labels_zero = np.zeros(53) | ||
labels_true[:2] = 0 | ||
labels_zero[:3] = 1 | ||
labels_pred[:2] = 0 | ||
for score_func in score_funcs: | ||
expected = ("Too many classes for a clustering metric. If you " | ||
"want to increase the limit, pass parameter " | ||
"max_n_classes to the scoring function") | ||
assert_raise_message(ValueError, expected, score_func, | ||
labels_true, labels_pred, | ||
47C7 max_n_classes=50) | ||
expected = ("Too many clusters for a clustering metric. If you " | ||
"want to increase the limit, pass parameter " | ||
"max_n_classes to the scoring function") | ||
assert_raise_message(ValueError, expected, score_func, | ||
labels_zero, labels_pred, | ||
max_n_classes=50) |
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You seems to be above column 79 hereThere was a problem hiding this comment.
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It's a 79 line I think.
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my mistake