GoogleCloudMlV1__ExplanationConfig

import type { GoogleCloudMlV1__ExplanationConfig } from "https://googleapis.deno.dev/v1/ml:v1.ts";

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. Learn more about feature attributions.

interface GoogleCloudMlV1__ExplanationConfig {

integratedGradientsAttribution?: GoogleCloudMlV1__IntegratedGradientsAttribution;

sampledShapleyAttribution?: GoogleCloudMlV1__SampledShapleyAttribution;

xraiAttribution?: GoogleCloudMlV1__XraiAttribution;

}

§Properties

integratedGradientsAttribution?: GoogleCloudMlV1__IntegratedGradientsAttribution

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Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

sampledShapleyAttribution?: GoogleCloudMlV1__SampledShapleyAttribution

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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.

xraiAttribution?: GoogleCloudMlV1__XraiAttribution

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Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.