Source code for caliber.binary_classification.metrics.rates
import numpy as np
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def false_positive_rate(targets: np.ndarray, preds: np.ndarray) -> float:
return np.mean(preds * (1 - targets)) / (1 - np.mean(targets))
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def false_negative_rate(targets: np.ndarray, preds: np.ndarray) -> float:
return np.mean((1 - preds) * targets) / np.mean(targets)
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def true_positive_rate(targets: np.ndarray, preds: np.ndarray) -> float:
return 1 - false_negative_rate(targets, preds)
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def true_negative_rate(targets: np.ndarray, preds: np.ndarray) -> float:
return 1 - false_positive_rate(targets, preds)