com.google.api.services.ml.v1.model

Class GoogleCloudMlV1ExplanationConfig

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.ml.v1.model.GoogleCloudMlV1ExplanationConfig

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class GoogleCloudMlV1ExplanationConfig
extends GenericJson

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.](/ai-platform/prediction/docs/ai- explanations/overview)

This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the AI Platform Training & Prediction API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

GenericData.Flags

Nested classes/interfaces inherited from class java.util.AbstractMap

AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>

Nested classes/interfaces inherited from interface java.util.Map

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
GoogleCloudMlV1ExplanationConfig()

Method Summary

Modifier and Type	Method and Description
GoogleCloudMlV1ExplanationConfig	clone()
GoogleCloudMlV1IntegratedGradientsAttribution	getIntegratedGradientsAttribution() Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure.
GoogleCloudMlV1SampledShapleyAttribution	getSampledShapleyAttribution() An attribution method that approximates Shapley values for features that contribute to the label being predicted.
GoogleCloudMlV1XraiAttribution	getXraiAttribution() Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure.
GoogleCloudMlV1ExplanationConfig	set(String fieldName, Object value)
GoogleCloudMlV1ExplanationConfig	setIntegratedGradientsAttribution(GoogleCloudMlV1IntegratedGradientsAttribution integratedGradientsAttribution) Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure.
GoogleCloudMlV1ExplanationConfig	setSampledShapleyAttribution(GoogleCloudMlV1SampledShapleyAttribution sampledShapleyAttribution) An attribution method that approximates Shapley values for features that contribute to the label being predicted.
GoogleCloudMlV1ExplanationConfig	setXraiAttribution(GoogleCloudMlV1XraiAttribution xraiAttribution) Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure.

Methods inherited from class com.google.api.client.json.GenericJson

getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData

entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

GoogleCloudMlV1ExplanationConfig

public GoogleCloudMlV1ExplanationConfig()

Method Detail

getIntegratedGradientsAttribution

public GoogleCloudMlV1IntegratedGradientsAttribution getIntegratedGradientsAttribution()

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

Returns:

value or null for none

setIntegratedGradientsAttribution

public GoogleCloudMlV1ExplanationConfig setIntegratedGradientsAttribution(GoogleCloudMlV1IntegratedGradientsAttribution 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

Parameters:

integratedGradientsAttribution - integratedGradientsAttribution or null for none

getSampledShapleyAttribution

public GoogleCloudMlV1SampledShapleyAttribution getSampledShapleyAttribution()

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.

Returns:

value or null for none

setSampledShapleyAttribution

public GoogleCloudMlV1ExplanationConfig setSampledShapleyAttribution(GoogleCloudMlV1SampledShapleyAttribution 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.

Parameters:

sampledShapleyAttribution - sampledShapleyAttribution or null for none

getXraiAttribution

public GoogleCloudMlV1XraiAttribution getXraiAttribution()

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.

Returns:

value or null for none

setXraiAttribution

public GoogleCloudMlV1ExplanationConfig setXraiAttribution(GoogleCloudMlV1XraiAttribution 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.

Parameters:

xraiAttribution - xraiAttribution or null for none

set

public GoogleCloudMlV1ExplanationConfig set(String fieldName,
                                            Object value)

Overrides:

set in class GenericJson

clone

public GoogleCloudMlV1ExplanationConfig clone()

Overrides:

clone in class GenericJson