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[MRG] Invariance test for non-scalar metric #10730

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Merged
merged 15 commits into from
Jun 30, 2018
Merged

[MRG] Invariance test for non-scalar metric #10730

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79c6c48
Support non-scalar output in metrics invariance tests
dmohns Feb 27, 2018
0d92ebb
Add curves to invariance tests
dmohns Feb 27, 2018
cb5e189
Apply invariance tests to curve metrics
dmohns Mar 2, 2018
2e002e6
Test sample weight invariance using approximation
dmohns Mar 2, 2018
42fd60b
Remove obsolete metrics tests
dmohns Mar 3, 2018
b928b59
Test confusion matrix with scaling
dmohns Mar 3, 2018
0e8126d
Make invariance tests more robust
dmohns Mar 4, 2018
94b9bd0
Sort imports alphabetically
dmohns Mar 4, 2018
e34d979
Revert to assert_equal for list asserts
dmohns May 24, 2018
3e6e3bf
Clarify unnormalized behaviour of confusion_matrix
dmohns May 24, 2018
fa5a011
Add alternative way to handle precision_recall_curve
dmohns May 24, 2018
3c05bd7
Merge branch 'master' into invariance-test-non-scalar-metric
dmohns Jun 28, 2018
b455464
Make padding more conspicuous
dmohns Jun 29, 2018
92296f3
Make metrics/test_common run with old NumPy versions
Jun 29, 2018
ef662bf
Make metrics/test_common run with ancient NumPy versions
Jun 29, 2018
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44 changes: 0 additions & 44 deletions sklearn/metrics/tests/test_classification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -667,50 +667,6 @@ def test_zero_precision_recall():
np.seterr(**old_error_settings)


def test_confusion_matrix_multiclass():
# Test confusion matrix - multi-class case
y_true, y_pred, _ = make_prediction(binary=False)

def test(y_true, y_pred, string_type=False):
# compute confusion matrix with default labels introspection
cm = confusion_matrix(y_true, y_pred)
assert_array_equal(cm, [[19, 4, 1],
[4, 3, 24],
[0, 2, 18]])

# compute confusion matrix with explicit label ordering
labels = ['0', '2', '1'] if string_type else [0, 2, 1]
cm = confusion_matrix(y_true,
y_pred,
labels=labels)
assert_array_equal(cm, [[19, 1, 4],
[0, 18, 2],
[4, 24, 3]])

test(y_true, y_pred)
test(list(str(y) for y in y_true),
list(str(y) for y in y_pred),
string_type=True)


def test_confusion_matrix_sample_weight():
"""Test confusion matrix - case with sample_weight"""
y_true, y_pred, _ = make_prediction(binary=False)

weights = [.1] * 25 + [.2] * 25 + [.3] * 25

cm = confusion_matrix(y_true, y_pred, sample_weight=weights)

true_cm = (.1 * confusion_matrix(y_true[:25], y_pred[:25]) +
.2 * confusion_matrix(y_true[25:50], y_pred[25:50]) +
.3 * confusion_matrix(y_true[50:], y_pred[50:]))

assert_array_almost_equal(cm, true_cm)
assert_raises(
ValueError, confusion_matrix, y_true, y_pred,
sample_weight=weights[:-1])


def test_confusion_matrix_multiclass_subset_labels():
# Test confusion matrix - multi-class case with subset of labels
y_true, y_pred, _ = make_prediction(binary=False)
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