ExplanationParameters class final

Parameters to configure explaining for Model's predictions.

Constructors

ExplanationParameters({SampledShapleyAttribution? sampledShapleyAttribution, IntegratedGradientsAttribution? integratedGradientsAttribution, XraiAttribution? xraiAttribution, Examples? examples, int topK = 0, ListValue? outputIndices})

ExplanationParameters.fromJson(Object? j)

factory

Properties

examples → Examples?

Example-based explanations that returns the nearest neighbors from the provided dataset.

final

hashCode → int

The hash code for this object.

no setter, inherited

integratedGradientsAttribution → IntegratedGradientsAttribution?

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

final

outputIndices → ListValue?

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining.

final

qualifiedName → String

The fully qualified name of this message, i.e., google.protobuf.Duration or google.rpc.ErrorInfo.

final, inherited

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

sampledShapleyAttribution → SampledShapleyAttribution?

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

final

topK → int

If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.

final

xraiAttribution → XraiAttribution?

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825

final

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

toJson() → Object

toString() → String

A string representation of this object.

override

Operators

operator ==(Object other) → bool

The equality operator.

inherited

Constants

fullyQualifiedName → const String