Explainer

Explainer Base

ExplainerBase(model[, x_train_orig, ...])
ExplainerBase.fit([x_train_orig, y_train])	Fit this explainer object.
ExplainerBase.produce([x_orig, ...])	Return the explanation, in the interpretable feature space with feature descriptions applied.
ExplainerBase.model_predict(x_orig)	Predict on x_orig using the model and return the result

Local Feature Contributions

LocalFeatureContribution(model[, ...])	Generic LocalFeatureContribution wrapper
LocalFeatureContribution.fit([x_train_orig, ...])	Fit this explainer object
LocalFeatureContribution.produce([x_orig, ...])	Return the explanation, in the interpretable feature space with feature descriptions applied.

Global Feature Importance

GlobalFeatureImportance(model[, ...])	Generic GlobalFeatureImportance wrapper
GlobalFeatureImportance.fit([x_train_orig, ...])	Fit this explainer object
GlobalFeatureImportance.produce([x_orig, ...])	Return the explanation, in the interpretable feature space with feature descriptions applied.

Decision Tree Explainer

DecisionTreeExplainer(model[, x_train_orig, ...])	Generic DecisionTreeExplainer wrapper
DecisionTreeExplainer.fit([x_train_orig, ...])	Fit this explainer object
DecisionTreeExplainer.produce([x_orig, ...])	Return the explanation, in the interpretable feature space with feature descriptions applied.

Partial Dependence Explainer

PartialDependenceExplainer(model, features)	Generic PartialDependence wrapper
PartialDependenceExplainer.fit([...])	Fit this explainer object
PartialDependenceExplainer.produce([x_orig, ...])	Return the explanation, in the interpretable feature space with feature descriptions applied.

Similiar Examples

SimilarExamples(model[, x_train_orig, ...])	SimilarExamples object.
SimilarExamples.fit([x_train_orig, y_train])	Fit the explainer
SimilarExamples.produce([x_orig, ...])	Return the explanation, in the interpretable feature space with feature descriptions applied.