SupervisedAnomalyDetector¶
A supervised anomaly detector.
Methods¶
learn_one
Update the model.
Parameters
- x (dict)
- y (Union[bool, str, int, numbers.Number])
Returns
SupervisedAnomalyDetector: self
score_one
Return an outlier score.
A high score is indicative of an anomaly. A low score corresponds a normal observation.
Parameters
- x (dict)
- y (Union[bool, str, int, numbers.Number])
Returns
float: An anomaly score. A high score is indicative of an anomaly. A low score corresponds a