mixmo.core.metrics_ensemble.ratio_errors

mixmo.core.metrics_ensemble.ratio_errors(y, y_pred1, y_pred2)

Calculates Ratio of errors diversity measure between a pair of classifiers. A higher value means that the base classifiers are less likely to make the same errors. The ratio must be maximized for a higher diversity

Parameters

• y (array of shape = [n_samples]:) – class labels of each sample.

• y_pred1 (array of shape = [n_samples]:) – predicted class labels by the classifier 1 for each sample.

• y_pred2 (array of shape = [n_samples]:) – predicted class labels by the classifier 2 for each sample.

Returns

ratio

Return type

The q-statistic measure between two classifiers

References

Aksela, Matti. “Comparison of classifier selection methods for improving committee performance.” Multiple Classifier Systems (2003): 159-159.