Source code for caliber.binary_classification.metrics.rates

import numpy as np


[docs] def false_positive_rate(targets: np.ndarray, preds: np.ndarray) -> float: return np.mean(preds * (1 - targets)) / (1 - np.mean(targets))
[docs] def false_negative_rate(targets: np.ndarray, preds: np.ndarray) -> float: return np.mean((1 - preds) * targets) / np.mean(targets)
[docs] def true_positive_rate(targets: np.ndarray, preds: np.ndarray) -> float: return 1 - false_negative_rate(targets, preds)
[docs] def true_negative_rate(targets: np.ndarray, preds: np.ndarray) -> float: return 1 - false_positive_rate(targets, preds)