Classification Metrics

The imbalanced_ensemble.metrics module includes score functions, performance metrics and pairwise metrics and distance computations.

sensitivity_specificity_support(y_true, ...)

Compute sensitivity, specificity, and support for each class

sensitivity_score(y_true, y_pred, *[, ...])

Compute the sensitivity

specificity_score(y_true, y_pred, *[, ...])

Compute the specificity

geometric_mean_score(y_true, y_pred, *[, ...])

Compute the geometric mean.

make_index_balanced_accuracy(*[, alpha, squared])

Balance any scoring function using the index balanced accuracy

classification_report_imbalanced(y_true, ...)

Build a classification report based on metrics used with imbalanced dataset

macro_averaged_mean_absolute_error(y_true, ...)

Compute Macro-Averaged Mean Absolute Error (MA-MAE) for imbalanced ordinal classification.