coverforest.metrics.average_set_size_loss

coverforest.metrics.average_set_size_loss(y_true, y_pred)

Compute the average size of classification prediction sets.

For each sample, the set size is the number of classes included in the prediction set (sum of binary indicators).

Parameters:

• y_true (array-like of shape (n_samples,)) – Ground truth (correct) labels.

• y_pred (tuple, list or array-like of shape (n_samples, n_classes)) – Binary matrix indicating the predicted set for each sample, where 1 indicates the class is included in the prediction set and 0 indicates it is not.

Returns:

score – Returns the average prediction set size. Minimum possible value is 0, maximum is n_classes.

Return type:

float

Examples

>>> import numpy as np
>>> from metrics import average_set_size_loss
>>> y_pred = np.array([[1, 0, 0], [1, 1, 0], [0, 0, 1]])
>>> average_set_size_loss(y_pred)
1.333...