DriftDetectionMetrics

class capymoa.drift.eval_detector.DriftDetectionMetrics

Bases: object

Metrics for evaluating drift detection performance.

__init__(

fp: int,

tp: int,

fn: int,

precision: float,

recall: float,

episode_recall: float,

f1: float,

mdt: float,

far: float,

ar: float,

n_episodes: int,

n_alarms: int,

) → None

ar: float

Alarm rate per EvaluateDriftDetector.rate_period instances

episode_recall: float

Recall score for drift episodes (in this case, a correct prediction of a drift episode is counted as 1 true positive).

f1: float

F1 score (harmonic mean of precision and recall).

far: float

False alarm rate per EvaluateDriftDetector.rate_period instances

fn: int

False negatives (missed drifts).

fp: int

False positives (incorrect detections).

mdt: float

Mean time to detect successful detections.

n_alarms: int

Total number of alarms raised

n_episodes: int

Total number of drift episodes

precision: float

Precision score (tp / (tp + fp)).

recall: float

Recall score (tp / (tp + fn)).

tp: int

True positives (correct detections).