alibi_detect.od.sklearn.base

FitMixinSklearn

Inherits from: ABC

Methods

check_fitted

check_fitted()

Checks to make sure object has been fitted.

fit

fit(x_ref: numpy.ndarray) -> typing_extensions.Self

Abstract fit method.

Name	Type	Default	Description
x_ref	numpy.ndarray
x			torch.Tensor to fit object on.

Returns

• Type: typing_extensions.Self

SklearnOutlierDetector

Inherits from: FitMixinSklearn, ABC

Base class for sklearn backend outlier detection algorithms.

Methods

check_threshold_inferred

check_threshold_inferred()

Check if threshold is inferred.

infer_threshold

infer_threshold(x: numpy.ndarray, fpr: float) -> None

Infer the threshold for the data. Prerequisite for outlier predictions.

Name	Type	Default	Description
x	numpy.ndarray		Data to infer the threshold for.
fpr	float		False positive rate to use for threshold inference.

Returns

• Type: None

predict

predict(x: numpy.ndarray) -> alibi_detect.od.sklearn.base.SklearnOutlierDetectorOutput

Predict outlier labels for the data.

Computes the outlier scores. If the detector is not fit on reference data we raise an error. If the threshold is inferred, the outlier labels and p-values are also computed and returned. Otherwise, the outlier labels and p-values are set to None.

Name	Type	Default	Description
x	numpy.ndarray		Data to predict.

Returns

• Type: alibi_detect.od.sklearn.base.SklearnOutlierDetectorOutput

score

score(x: numpy.ndarray) -> numpy.ndarray

Score the data.

Name	Type	Default	Description
x	numpy.ndarray		Data to score.

Returns

• Type: numpy.ndarray

SklearnOutlierDetectorOutput

Output of the outlier detector.

Fields

Field	Type	Default
threshold_inferred	bool	``
instance_score	numpy.ndarray	``
threshold	Optional[numpy.ndarray]	``
is_outlier	Optional[numpy.ndarray]	``
p_value	Optional[numpy.ndarray]	``

Constructor

SklearnOutlierDetectorOutput(self, threshold_inferred: bool, instance_score: numpy.ndarray, threshold: Optional[numpy.ndarray], is_outlier: Optional[numpy.ndarray], p_value: Optional[numpy.ndarray]) -> None

Name	Type	Default	Description
threshold_inferred	bool
instance_score	numpy.ndarray
threshold	Optional[numpy.ndarray]
is_outlier	Optional[numpy.ndarray]
p_value	Optional[numpy.ndarray]