pyreal.explanation_types.decision_tree.DecisionTreeExplanation

class pyreal.explanation_types.decision_tree.DecisionTreeExplanation(explanation, values=None, other_properties=None)

A type wrapper for decision-tree based type outputs from explanation algorithms.

__init__(explanation, values=None, other_properties=None)

Set the wrapped explanation to explanation and values to values and validate :param explanation: wrapped explanation :type explanation: object :param values: Values corresponding with the object being explained :type values: DataFrame of shape (n_instances, n_features) or None :param other_properties: Other information relevant to the explanation :type other_properties: dict

Methods

__init__(explanation[, values, other_properties])	Set the wrapped explanation to explanation and values to values and validate :param explanation: wrapped explanation :type explanation: object :param values: Values corresponding with the object being explained :type values: DataFrame of shape (n_instances, n_features) or None :param other_properties: Other information relevant to the explanation :type other_properties: dict
apply_feature_descriptions(feature_descriptions)	Apply feature descriptions to explanation and values
get()	Get the explanation wrapped by this type.
get_all()	Get the explanation and wrapped values as a tuple.
get_explanation()	Get the explanation wrapped by this type
get_values()	Return the values associated with the explanation
update_explanation(new_explanation[, ...])	Sets this object's explanation to the new value.
update_values(values[, inplace])	Updates this objects values, and validates
validate()	Validate that self.explanation is a valid and fitted sklearn DecisionTree :returns: None
validate_other_properties()	Validate that any additional properties are valid
validate_values()	Validate that self.values are valid values for this Explanation.