Uses of Class
com.google.cloud.aiplatform.v1beta1.ExplanationParameters.Builder

Packages that use ExplanationParameters.Builder

Package	Description
com.google.cloud.aiplatform.v1beta1	A client to Vertex AI API

Uses of ExplanationParameters.Builder in com.google.cloud.aiplatform.v1beta1

Methods in com.google.cloud.aiplatform.v1beta1 that return ExplanationParameters.Builder

Modifier and Type	Method	Description
ExplanationParameters.Builder	ExplanationParameters.Builder.addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
ExplanationParameters.Builder	ExplanationParameters.Builder.clear()
ExplanationParameters.Builder	ExplanationParameters.Builder.clearExamples()	Example-based explanations that returns the nearest neighbors from the provided dataset.
ExplanationParameters.Builder	ExplanationParameters.Builder.clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
ExplanationParameters.Builder	ExplanationParameters.Builder.clearIntegratedGradientsAttribution()	An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.Builder.clearMethod()
ExplanationParameters.Builder	ExplanationParameters.Builder.clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
ExplanationParameters.Builder	ExplanationParameters.Builder.clearOutputIndices()	If populated, only returns attributions that have [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] contained in output_indices.
ExplanationParameters.Builder	ExplanationParameters.Builder.clearSampledShapleyAttribution()	An attribution method that approximates Shapley values for features that contribute to the label being predicted.
ExplanationParameters.Builder	ExplanationParameters.Builder.clearTopK()	If populated, returns attributions for top K indices of outputs (defaults to 1).
ExplanationParameters.Builder	ExplanationParameters.Builder.clearXraiAttribution()	An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.Builder.clone()
ExplanationParameters.Builder	ExplanationSpec.Builder.getParametersBuilder()	Required.
ExplanationParameters.Builder	ExplanationSpecOverride.Builder.getParametersBuilder()	The parameters to be overridden.
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeExamples(Examples value)	Example-based explanations that returns the nearest neighbors from the provided dataset.
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeFrom(ExplanationParameters other)
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeFrom(com.google.protobuf.Message other)
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeIntegratedGradientsAttribution(IntegratedGradientsAttribution value)	An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeOutputIndices(com.google.protobuf.ListValue value)	If populated, only returns attributions that have [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] contained in output_indices.
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeSampledShapleyAttribution(SampledShapleyAttribution value)	An attribution method that approximates Shapley values for features that contribute to the label being predicted.
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
ExplanationParameters.Builder	ExplanationParameters.Builder.mergeXraiAttribution(XraiAttribution value)	An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure.
static ExplanationParameters.Builder	ExplanationParameters.newBuilder()
static ExplanationParameters.Builder	ExplanationParameters.newBuilder(ExplanationParameters prototype)
ExplanationParameters.Builder	ExplanationParameters.newBuilderForType()
protected ExplanationParameters.Builder	ExplanationParameters.newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)
ExplanationParameters.Builder	ExplanationParameters.Builder.setExamples(Examples value)	Example-based explanations that returns the nearest neighbors from the provided dataset.
ExplanationParameters.Builder	ExplanationParameters.Builder.setExamples(Examples.Builder builderForValue)	Example-based explanations that returns the nearest neighbors from the provided dataset.
ExplanationParameters.Builder	ExplanationParameters.Builder.setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
ExplanationParameters.Builder	ExplanationParameters.Builder.setIntegratedGradientsAttribution(IntegratedGradientsAttribution value)	An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.Builder.setIntegratedGradientsAttribution(IntegratedGradientsAttribution.Builder builderForValue)	An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.Builder.setOutputIndices(com.google.protobuf.ListValue value)	If populated, only returns attributions that have [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] contained in output_indices.
ExplanationParameters.Builder	ExplanationParameters.Builder.setOutputIndices(com.google.protobuf.ListValue.Builder builderForValue)	If populated, only returns attributions that have [output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] contained in output_indices.
ExplanationParameters.Builder	ExplanationParameters.Builder.setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
ExplanationParameters.Builder	ExplanationParameters.Builder.setSampledShapleyAttribution(SampledShapleyAttribution value)	An attribution method that approximates Shapley values for features that contribute to the label being predicted.
ExplanationParameters.Builder	ExplanationParameters.Builder.setSampledShapleyAttribution(SampledShapleyAttribution.Builder builderForValue)	An attribution method that approximates Shapley values for features that contribute to the label being predicted.
ExplanationParameters.Builder	ExplanationParameters.Builder.setTopK(int value)	If populated, returns attributions for top K indices of outputs (defaults to 1).
ExplanationParameters.Builder	ExplanationParameters.Builder.setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
ExplanationParameters.Builder	ExplanationParameters.Builder.setXraiAttribution(XraiAttribution value)	An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.Builder.setXraiAttribution(XraiAttribution.Builder builderForValue)	An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure.
ExplanationParameters.Builder	ExplanationParameters.toBuilder()

Methods in com.google.cloud.aiplatform.v1beta1 with parameters of type ExplanationParameters.Builder

Modifier and Type	Method	Description
ExplanationSpec.Builder	ExplanationSpec.Builder.setParameters(ExplanationParameters.Builder builderForValue)	Required.
ExplanationSpecOverride.Builder	ExplanationSpecOverride.Builder.setParameters(ExplanationParameters.Builder builderForValue)	The parameters to be overridden.