PSI#

class frouros.detectors.data_drift.batch.distance_based.PSI(num_bins: int = 10, callbacks: Optional[Union[BaseCallbackBatch, List[BaseCallbackBatch]]] = None)#

PSI (Population Stability Index) [wu2010enterprise] detector.

References:

[wu2010enterprise]

Wu, Desheng, and David L. Olson. “Enterprise risk management: coping with model risk in a large bank.” Journal of the Operational Research Society 61.2 (2010): 179-190.

property num_bins: int#

Number of bins property.

Returns:

number of bins in which to divide probabilities

Return type:

int

property X_ref: Optional[ndarray]#

Reference data property.

Returns:

reference data

Return type:

Optional[numpy.ndarray]

property callbacks: Optional[List[BaseCallback]]#

Callbacks property.

Returns:

callbacks

Return type:

Optional[List[BaseCallback]]

compare(X: ndarray, **kwargs) Tuple[ndarray, Dict[str, Any]]#

Compare values.

Parameters:

X (numpy.ndarray) – feature data

Returns:

compare result and callbacks logs

Return type:

Tuple[numpy.ndarray, Dict[str, Any]]

property data_type: BaseDataType#

Data type property.

Returns:

data type

Return type:

BaseDataType

fit(X: ndarray, **kwargs) Dict[str, Any]#

Fit detector.

Parameters:

X (numpy.ndarray) – feature data

Returns:

callbacks logs

Return type:

Dict[str, Any]

reset() None#

Reset method.

property statistical_kwargs: Dict[str, Any]#

Statistical kwargs property.

Returns:

statistical kwargs

Return type:

Dict[str, Any]

property statistical_method: Callable#

Statistical method property.

Returns:

statistical method

Return type:

Callable

property statistical_type: BaseStatisticalType#

Statistical type property.

Returns:

statistical type

Return type:

BaseStatisticalType