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|
| import pytest |
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|
| import fairlearn.metrics as metrics |
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| def test_selection_rate_unweighted(): |
| y_true = [0, 0, 0, 0, 0, 0, 0, 0] |
| y_pred = [0, 0, 0, 1, 1, 1, 1, 1] |
|
|
| result = metrics.selection_rate(y_true, y_pred) |
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| assert result == 0.625 |
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| def test_selection_rate_weighted(): |
| y_true = [0, 0, 0, 0, 0, 0, 0, 0] |
| y_pred = [0, 1, 1, 0, 0, 0, 0, 0] |
| weight = [1, 2, 3, 4, 1, 2, 1, 2] |
|
|
| result = metrics.selection_rate(y_true, y_pred, sample_weight=weight) |
|
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| assert result == 0.3125 |
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|
|
| def test_selection_rate_non_numeric(): |
| a = "a" |
| b = "b" |
| y_true = [a, b, a, b, a, b, a, b] |
| y_pred = [a, a, a, b, b, b, a, a] |
|
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| result = metrics.selection_rate(y_true, y_pred, pos_label=b) |
|
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| assert result == 0.375 |
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|
|
| def test_group_selection_rate(): |
| a = "a" |
| b = "b" |
| q = "q" |
| r = "r" |
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|
| y_true = [a, b, a, b, b, b, a, a] |
| y_pred = [a, b, a, a, b, b, a, b] |
| weight = [1, 2, 3, 4, 1, 2, 4, 8] |
| groups = [r, r, r, r, q, q, q, q] |
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| result = metrics.group_selection_rate(y_true, y_pred, groups, |
| pos_label=b, |
| sample_weight=weight) |
|
|
| assert result.overall == 0.52 |
| assert result.by_group[r] == 0.2 |
| assert result.by_group[q] == pytest.approx(0.73333333) |
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|
