Struct google_ml1::api::GoogleCloudMlV1__ExplanationConfig[][src]

pub struct GoogleCloudMlV1__ExplanationConfig {
    pub integrated_gradients_attribution: Option<GoogleCloudMlV1__IntegratedGradientsAttribution>,
    pub sampled_shapley_attribution: Option<GoogleCloudMlV1__SampledShapleyAttribution>,
    pub xrai_attribution: Option<GoogleCloudMlV1__XraiAttribution>,
}

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.

This type is not used in any activity, and only used as part of another schema.

Fields

integrated_gradients_attribution: Option<GoogleCloudMlV1__IntegratedGradientsAttribution>

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

sampled_shapley_attribution: Option<GoogleCloudMlV1__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.

xrai_attribution: Option<GoogleCloudMlV1__XraiAttribution>

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.

Trait Implementations

impl Clone for GoogleCloudMlV1__ExplanationConfig[src]

impl Debug for GoogleCloudMlV1__ExplanationConfig[src]

impl Default for GoogleCloudMlV1__ExplanationConfig[src]

impl<'de> Deserialize<'de> for GoogleCloudMlV1__ExplanationConfig[src]

impl Part for GoogleCloudMlV1__ExplanationConfig[src]

impl Serialize for GoogleCloudMlV1__ExplanationConfig[src]

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