classification_threshold

empulse.metrics.classification_threshold(y_true, y_score, customer_threshold)

Return classification threshold for given customer threshold.

Parameters:

y_true1D array-like, shape=(n_samples,)

Binary target values (‘positive’: 1, ‘negative’: 0).

y_score1D array-like, shape=(n_samples,)

Target scores, can either be probability estimates or non-thresholded decision values.

customer_thresholdfloat

Customer threshold determined by value-driven metric.

Returns:

thresholdfloat

Classification threshold for given customer threshold.

Examples

>>> from empulse.metrics import classification_threshold
>>> from empulse.metrics import empc
>>> y_true = [0, 1, 0, 1, 0, 1, 0, 1]
>>> y_score = [0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.8, 0.9]
>>> score, threshold = empc(y_true, y_score)
>>> classification_threshold(y_true, y_score, threshold)
0.2