facet.explanation.FunctionExplainerFactory#

class facet.explanation.FunctionExplainerFactory(**explainer_kwargs)[source]#

A factory constructing Explainer instances that use Python functions as the underlying model.

Bases: ExplainerFactory [Union [RegressorMixin, ClassifierMixin, Callable [[typing.Union[pandas.core.series.Series, pandas.core.frame.DataFrame, numpy.ndarray[typing.Any, numpy.dtype[numpy.float64]]]], Union [Series, ndarray [Any, dtype [float64]], float]]]]
Metaclasses: ABCMeta
Parameters: explainer_kwargs (Any) – additional keyword arguments to be passed to the explainer

Method summary

`make_explainer`	Construct a new `Explainer` to compute shap values.
`make_explainer_from_function`	Construct an explainer from a function.
`to_expression`	See `pytools.expression.HasExpressionRepr.to_expression()`

Attribute summary

`explains_raw_output`	`True` if explainers made by this factory explain raw model output, `False` otherwise.
`supports_shap_interaction_values`	`True` if explainers made by this factory allow for calculating SHAP interaction values, `False` otherwise.
`uses_background_dataset`	`True`, since function explainers typically use a background dataset
`explainer_kwargs`	Additional keyword arguments to be passed to the explainer constructor.

Definitions

make_explainer(model, data)[source]#

Construct a new Explainer to compute shap values.

Parameters

model (Union[RegressorMixin, ClassifierMixin, Callable[[Union[Series, DataFrame, ndarray[Any, dtype[float64]]]], Union[Series, ndarray[Any, dtype[float64]], float]]]) – fitted learner for which to compute shap values
data (Optional[DataFrame]) – background dataset (optional)

Return type

BaseExplainer

Returns

the new explainer instance

abstract make_explainer_from_function(model_fn, data)[source]#

Construct an explainer from a function.

Parameters

model_fn (Callable[[Union[Series, DataFrame, ndarray[Any, dtype[float64]]]], Union[Series, ndarray[Any, dtype[float64]], float]]) – the function representing the model
data (Optional[DataFrame]) – the background dataset

Return type

BaseExplainer

Returns

the explainer

abstract to_expression()#: See pytools.expression.HasExpressionRepr.to_expression()

abstract property explains_raw_output: bool#

True if explainers made by this factory explain raw model output, False otherwise.

abstract property supports_shap_interaction_values: bool#

True if explainers made by this factory allow for calculating SHAP interaction values, False otherwise.

property uses_background_dataset: bool#

True, since function explainers typically use a background dataset

facet.explanation.ExactExplainerFactory

facet.explanation.KernelExplainerFactory