AnomalyDetectionEvaluator#

class capymoa.evaluation.AnomalyDetectionEvaluator[source]#

Bases: object

Wrapper for the Anomaly (AUC) Performance Evaluator from MOA. By default, it uses the BasicAUCImbalancedPerformanceEvaluator

__init__(
schema: Schema = None,
window_size=None,
)[source]#
get_instances_seen()[source]#
update(y_target_index: int, score: float)[source]#

Update the evaluator with the ground-truth and the prediction.

Parameters:

  • y_target_index – The ground-truth class index. This is NOT the actual class value, but the index of the class value in the schema.

  • score – The predicted scores. Should be in the range [0, 1].

metrics_header()[source]#
metrics()[source]#
metrics_dict()[source]#
metrics_per_window()[source]#
auc()[source]#
s_auc()[source]#