pysad.transform.ensemble.AverageScoreEnsembler¶

class pysad.transform.ensemble.AverageScoreEnsembler(estimator_weights=None)[source]¶

An wrapper class that results in the weighted average of the anomaly scores from multiple anomaly detectors. For more details, see PyOD documentation.

Parameters:: estimator_weights (np array of shape (1, num_anomaly_detectors)) – The weights for detectors. If None, uniform weights are assigned.

Methods

`__init__`([estimator_weights])
`fit`(scores)	Shortcut method that iteratively applies fit_partial to all instances in order.
`fit_partial`(scores)	Fits particular (next) timestep's score to train the ensembler.
`fit_transform`(scores)	Shortcut method that iteratively applies fit_transform_partial to all instances in order.
`fit_transform_partial`(score)	Shortcut method that iteratively applies fit_partial and transform_partial, respectively.
`transform`(scores)	Shortcut method that iteratively applies transform_partial to all instances in order.
`transform_partial`(scores)	Combines anomaly scores from multiple anomaly detectors for a particular timestep.

fit(scores)¶

Shortcut method that iteratively applies fit_partial to all instances in order.

Parameters:: shape (np.float64 array of) – Input scores.
Returns:: self.
Return type:: object

fit_partial(scores)¶

Fits particular (next) timestep’s score to train the ensembler. For PYOD based ensemblers, this method does not affect anything and returns self directly.

Parameters:: scores – np.float64 array of shape (num_anomaly_detectors, ) List of scores from multiple anomaly detectors.
Returns:: The fitted ensembler.
Return type:: object

fit_transform(scores)¶

Shortcut method that iteratively applies fit_transform_partial to all instances in order.

Parameters:: shape (np.float64 array of) – Input scores.
Returns:: Processed scores.
Return type:: np.float64 array of shape (num_instances,)

fit_transform_partial(score)¶

Shortcut method that iteratively applies fit_partial and transform_partial, respectively.

Parameters:: score (float) – Input score.
Returns:: Processed score.
Return type:: float

transform(scores)¶

Shortcut method that iteratively applies transform_partial to all instances in order.

Parameters:: shape (np.float64 array of) – Input scores.
Returns:: Processed scores.
Return type:: np.float64 array of shape (num_instances,)

transform_partial(scores)¶

Combines anomaly scores from multiple anomaly detectors for a particular timestep.

Parameters:: scores – np.float64 array of shape (num_anomaly_detectors, ) List of scores from multiple anomaly detectors.
Returns:: Resulting anomaly score.
Return type:: float