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fc0f7bd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import fairlearn.metrics as metrics
# ==============================================
# Specificity (aka True Negative Rate)
def test_specificity_all_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [0, 0, 0, 0, 1]
result = metrics.specificity_score(y_true, y_pred)
assert result == 1
def test_specificity_none_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [1, 1, 1, 1, 0]
result = metrics.specificity_score(y_true, y_pred)
assert result == 0
def test_specificity_some_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [0, 0, 0, 1, 1]
result = metrics.specificity_score(y_true, y_pred)
assert result == 0.75
def test_specificity_some_correct_with_false_negative():
y_true = [0, 0, 0, 0, 1]
y_pred = [0, 0, 1, 0, 0]
result = metrics.specificity_score(y_true, y_pred)
assert result == 0.75
# ========================================
# miss score (aka False Negative Rate)
def test_miss_all_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [0, 0, 0, 0, 1]
result = metrics.miss_rate(y_true, y_pred)
assert result == 0
def test_miss_none_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [1, 1, 1, 1, 0]
result = metrics.miss_rate(y_true, y_pred)
assert result == 1
def test_miss_with_false_positive():
y_true = [0, 0, 0, 0, 1]
y_pred = [0, 0, 0, 1, 1]
result = metrics.miss_rate(y_true, y_pred)
assert result == 0
def test_miss_some_correct():
y_true = [1, 1, 1, 1, 0, 0]
y_pred = [0, 0, 1, 0, 0, 1]
result = metrics.miss_rate(y_true, y_pred)
assert result == 0.75
# ============================
# Fall-out (aka False Positive Rate)
def test_fallout_all_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [0, 0, 0, 0, 1]
result = metrics.fallout_rate(y_true, y_pred)
assert result == 0
def test_fallout_none_correct():
y_true = [0, 0, 0, 0, 1]
y_pred = [1, 1, 1, 1, 0]
result = metrics.fallout_rate(y_true, y_pred)
assert result == 1
def test_fallout_some_correct():
y_true = [0, 0, 0, 0, 1, 1, 1]
y_pred = [0, 1, 1, 0, 0, 1, 0]
result = metrics.fallout_rate(y_true, y_pred)
assert result == 0.5
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