Class ModelEvaluation.Builder (3.4.2)

Version 3.4.2

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public static final class ModelEvaluation.Builder extends GeneratedMessageV3.Builder<ModelEvaluation.Builder> implements ModelEvaluationOrBuilder

A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.

Protobuf type google.cloud.aiplatform.v1beta1.ModelEvaluation

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelEvaluation.Builder

Implements

ModelEvaluationOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

Methods

addAllExplanationSpecs(Iterable<? extends ModelEvaluation.ModelEvaluationExplanationSpec> values)

public ModelEvaluation.Builder addAllExplanationSpecs(Iterable<? extends ModelEvaluation.ModelEvaluationExplanationSpec> values)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
values	Iterable<? extends com.google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec>

Returns

Type	Description
ModelEvaluation.Builder

addAllSliceDimensions(Iterable<String> values)

public ModelEvaluation.Builder addAllSliceDimensions(Iterable<String> values)

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Parameter

Name	Description
values	Iterable<String> The sliceDimensions to add.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

addExplanationSpecs(ModelEvaluation.ModelEvaluationExplanationSpec value)

public ModelEvaluation.Builder addExplanationSpecs(ModelEvaluation.ModelEvaluationExplanationSpec value)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
value	ModelEvaluation.ModelEvaluationExplanationSpec

Returns

Type	Description
ModelEvaluation.Builder

addExplanationSpecs(ModelEvaluation.ModelEvaluationExplanationSpec.Builder builderForValue)

public ModelEvaluation.Builder addExplanationSpecs(ModelEvaluation.ModelEvaluationExplanationSpec.Builder builderForValue)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
builderForValue	ModelEvaluation.ModelEvaluationExplanationSpec.Builder

Returns

Type	Description
ModelEvaluation.Builder

addExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec value)

public ModelEvaluation.Builder addExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec value)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameters

Name	Description
index	int
value	ModelEvaluation.ModelEvaluationExplanationSpec

Returns

Type	Description
ModelEvaluation.Builder

addExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec.Builder builderForValue)

public ModelEvaluation.Builder addExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec.Builder builderForValue)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameters

Name	Description
index	int
builderForValue	ModelEvaluation.ModelEvaluationExplanationSpec.Builder

Returns

Type	Description
ModelEvaluation.Builder

addExplanationSpecsBuilder()

public ModelEvaluation.ModelEvaluationExplanationSpec.Builder addExplanationSpecsBuilder()

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Returns

Type	Description
ModelEvaluation.ModelEvaluationExplanationSpec.Builder

addExplanationSpecsBuilder(int index)

public ModelEvaluation.ModelEvaluationExplanationSpec.Builder addExplanationSpecsBuilder(int index)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
index	int

Returns

Type	Description
ModelEvaluation.ModelEvaluationExplanationSpec.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ModelEvaluation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

addSliceDimensions(String value)

public ModelEvaluation.Builder addSliceDimensions(String value)

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Parameter

Name	Description
value	String The sliceDimensions to add.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

addSliceDimensionsBytes(ByteString value)

public ModelEvaluation.Builder addSliceDimensionsBytes(ByteString value)

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Parameter

Name	Description
value	ByteString The bytes of the sliceDimensions to add.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

build()

public ModelEvaluation build()

Returns

Type	Description
ModelEvaluation

buildPartial()

public ModelEvaluation buildPartial()

Returns

Type	Description
ModelEvaluation

clear()

public ModelEvaluation.Builder clear()

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearCreateTime()

public ModelEvaluation.Builder clearCreateTime()

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
ModelEvaluation.Builder

clearDisplayName()

public ModelEvaluation.Builder clearDisplayName()

The display name of the ModelEvaluation.

string display_name = 10;

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

clearExplanationSpecs()

public ModelEvaluation.Builder clearExplanationSpecs()

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Returns

Type	Description
ModelEvaluation.Builder

clearField(Descriptors.FieldDescriptor field)

public ModelEvaluation.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearMetadata()

public ModelEvaluation.Builder clearMetadata()

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Returns

Type	Description
ModelEvaluation.Builder

clearMetrics()

public ModelEvaluation.Builder clearMetrics()

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Returns

Type	Description
ModelEvaluation.Builder

clearMetricsSchemaUri()

public ModelEvaluation.Builder clearMetricsSchemaUri()

Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

string metrics_schema_uri = 2;

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

clearModelExplanation()

public ModelEvaluation.Builder clearModelExplanation()

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Returns

Type	Description
ModelEvaluation.Builder

clearName()

public ModelEvaluation.Builder clearName()

Output only. The resource name of the ModelEvaluation.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public ModelEvaluation.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearSliceDimensions()

public ModelEvaluation.Builder clearSliceDimensions()

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

clone()

public ModelEvaluation.Builder clone()

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getCreateTime()

public Timestamp getCreateTime()

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
Timestamp	The createTime.

getCreateTimeBuilder()

public Timestamp.Builder getCreateTimeBuilder()

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
Builder

getCreateTimeOrBuilder()

public TimestampOrBuilder getCreateTimeOrBuilder()

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
TimestampOrBuilder

getDefaultInstanceForType()

public ModelEvaluation getDefaultInstanceForType()

Returns

Type	Description
ModelEvaluation

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDisplayName()

public String getDisplayName()

The display name of the ModelEvaluation.

string display_name = 10;

Returns

Type	Description
String	The displayName.

getDisplayNameBytes()

public ByteString getDisplayNameBytes()

The display name of the ModelEvaluation.

string display_name = 10;

Returns

Type	Description
ByteString	The bytes for displayName.

getExplanationSpecs(int index)

public ModelEvaluation.ModelEvaluationExplanationSpec getExplanationSpecs(int index)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
index	int

Returns

Type	Description
ModelEvaluation.ModelEvaluationExplanationSpec

getExplanationSpecsBuilder(int index)

public ModelEvaluation.ModelEvaluationExplanationSpec.Builder getExplanationSpecsBuilder(int index)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
index	int

Returns

Type	Description
ModelEvaluation.ModelEvaluationExplanationSpec.Builder

getExplanationSpecsBuilderList()

public List<ModelEvaluation.ModelEvaluationExplanationSpec.Builder> getExplanationSpecsBuilderList()

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Returns

Type	Description
List<Builder>

getExplanationSpecsCount()

public int getExplanationSpecsCount()

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Returns

Type	Description
int

getExplanationSpecsList()

public List<ModelEvaluation.ModelEvaluationExplanationSpec> getExplanationSpecsList()

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Returns

Type	Description
List<ModelEvaluationExplanationSpec>

getExplanationSpecsOrBuilder(int index)

public ModelEvaluation.ModelEvaluationExplanationSpecOrBuilder getExplanationSpecsOrBuilder(int index)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
index	int

Returns

Type	Description
ModelEvaluation.ModelEvaluationExplanationSpecOrBuilder

getExplanationSpecsOrBuilderList()

public List<? extends ModelEvaluation.ModelEvaluationExplanationSpecOrBuilder> getExplanationSpecsOrBuilderList()

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Returns

Type	Description
List<? extends com.google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpecOrBuilder>

getMetadata()

public Value getMetadata()

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Returns

Type	Description
Value	The metadata.

getMetadataBuilder()

public Value.Builder getMetadataBuilder()

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Returns

Type	Description
Builder

getMetadataOrBuilder()

public ValueOrBuilder getMetadataOrBuilder()

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Returns

Type	Description
ValueOrBuilder

getMetrics()

public Value getMetrics()

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Returns

Type	Description
Value	The metrics.

getMetricsBuilder()

public Value.Builder getMetricsBuilder()

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Returns

Type	Description
Builder

getMetricsOrBuilder()

public ValueOrBuilder getMetricsOrBuilder()

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Returns

Type	Description
ValueOrBuilder

getMetricsSchemaUri()

public String getMetricsSchemaUri()

Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

string metrics_schema_uri = 2;

Returns

Type	Description
String	The metricsSchemaUri.

getMetricsSchemaUriBytes()

public ByteString getMetricsSchemaUriBytes()

Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

string metrics_schema_uri = 2;

Returns

Type	Description
ByteString	The bytes for metricsSchemaUri.

getModelExplanation()

public ModelExplanation getModelExplanation()

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Returns

Type	Description
ModelExplanation	The modelExplanation.

getModelExplanationBuilder()

public ModelExplanation.Builder getModelExplanationBuilder()

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Returns

Type	Description
ModelExplanation.Builder

getModelExplanationOrBuilder()

public ModelExplanationOrBuilder getModelExplanationOrBuilder()

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Returns

Type	Description
ModelExplanationOrBuilder

getName()

public String getName()

Output only. The resource name of the ModelEvaluation.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
String	The name.

getNameBytes()

public ByteString getNameBytes()

Output only. The resource name of the ModelEvaluation.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
ByteString	The bytes for name.

getSliceDimensions(int index)

public String getSliceDimensions(int index)

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Parameter

Name	Description
index	int The index of the element to return.

Returns

Type	Description
String	The sliceDimensions at the given index.

getSliceDimensionsBytes(int index)

public ByteString getSliceDimensionsBytes(int index)

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Parameter

Name	Description
index	int The index of the value to return.

Returns

Type	Description
ByteString	The bytes of the sliceDimensions at the given index.

getSliceDimensionsCount()

public int getSliceDimensionsCount()

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Returns

Type	Description
int	The count of sliceDimensions.

getSliceDimensionsList()

public ProtocolStringList getSliceDimensionsList()

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Returns

Type	Description
ProtocolStringList	A list containing the sliceDimensions.

hasCreateTime()

public boolean hasCreateTime()

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
boolean	Whether the createTime field is set.

hasMetadata()

public boolean hasMetadata()

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Returns

Type	Description
boolean	Whether the metadata field is set.

hasMetrics()

public boolean hasMetrics()

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Returns

Type	Description
boolean	Whether the metrics field is set.

hasModelExplanation()

public boolean hasModelExplanation()

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Returns

Type	Description
boolean	Whether the modelExplanation field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeCreateTime(Timestamp value)

public ModelEvaluation.Builder mergeCreateTime(Timestamp value)

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
ModelEvaluation.Builder

mergeFrom(ModelEvaluation other)

public ModelEvaluation.Builder mergeFrom(ModelEvaluation other)

Parameter

Name	Description
other	ModelEvaluation

Returns

Type	Description
ModelEvaluation.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ModelEvaluation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
ModelEvaluation.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public ModelEvaluation.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
ModelEvaluation.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeMetadata(Value value)

public ModelEvaluation.Builder mergeMetadata(Value value)

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Parameter

Name	Description
value	Value

Returns

Type	Description
ModelEvaluation.Builder

mergeMetrics(Value value)

public ModelEvaluation.Builder mergeMetrics(Value value)

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Parameter

Name	Description
value	Value

Returns

Type	Description
ModelEvaluation.Builder

mergeModelExplanation(ModelExplanation value)

public ModelEvaluation.Builder mergeModelExplanation(ModelExplanation value)

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Parameter

Name	Description
value	ModelExplanation

Returns

Type	Description
ModelEvaluation.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ModelEvaluation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

removeExplanationSpecs(int index)

public ModelEvaluation.Builder removeExplanationSpecs(int index)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameter

Name	Description
index	int

Returns

Type	Description
ModelEvaluation.Builder

setCreateTime(Timestamp value)

public ModelEvaluation.Builder setCreateTime(Timestamp value)

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
ModelEvaluation.Builder

setCreateTime(Timestamp.Builder builderForValue)

public ModelEvaluation.Builder setCreateTime(Timestamp.Builder builderForValue)

Output only. Timestamp when this ModelEvaluation was created.

.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
ModelEvaluation.Builder

setDisplayName(String value)

public ModelEvaluation.Builder setDisplayName(String value)

The display name of the ModelEvaluation.

string display_name = 10;

Parameter

Name	Description
value	String The displayName to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setDisplayNameBytes(ByteString value)

public ModelEvaluation.Builder setDisplayNameBytes(ByteString value)

The display name of the ModelEvaluation.

string display_name = 10;

Parameter

Name	Description
value	ByteString The bytes for displayName to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec value)

public ModelEvaluation.Builder setExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec value)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameters

Name	Description
index	int
value	ModelEvaluation.ModelEvaluationExplanationSpec

Returns

Type	Description
ModelEvaluation.Builder

setExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec.Builder builderForValue)

public ModelEvaluation.Builder setExplanationSpecs(int index, ModelEvaluation.ModelEvaluationExplanationSpec.Builder builderForValue)

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

repeated .google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec explanation_specs = 9;

Parameters

Name	Description
index	int
builderForValue	ModelEvaluation.ModelEvaluationExplanationSpec.Builder

Returns

Type	Description
ModelEvaluation.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public ModelEvaluation.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setMetadata(Value value)

public ModelEvaluation.Builder setMetadata(Value value)

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Parameter

Name	Description
value	Value

Returns

Type	Description
ModelEvaluation.Builder

setMetadata(Value.Builder builderForValue)

public ModelEvaluation.Builder setMetadata(Value.Builder builderForValue)

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path".

.google.protobuf.Value metadata = 11;

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
ModelEvaluation.Builder

setMetrics(Value value)

public ModelEvaluation.Builder setMetrics(Value value)

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Parameter

Name	Description
value	Value

Returns

Type	Description
ModelEvaluation.Builder

setMetrics(Value.Builder builderForValue)

public ModelEvaluation.Builder setMetrics(Value.Builder builderForValue)

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

.google.protobuf.Value metrics = 3;

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
ModelEvaluation.Builder

setMetricsSchemaUri(String value)

public ModelEvaluation.Builder setMetricsSchemaUri(String value)

Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

string metrics_schema_uri = 2;

Parameter

Name	Description
value	String The metricsSchemaUri to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setMetricsSchemaUriBytes(ByteString value)

public ModelEvaluation.Builder setMetricsSchemaUriBytes(ByteString value)

Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

string metrics_schema_uri = 2;

Parameter

Name	Description
value	ByteString The bytes for metricsSchemaUri to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setModelExplanation(ModelExplanation value)

public ModelEvaluation.Builder setModelExplanation(ModelExplanation value)

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Parameter

Name	Description
value	ModelExplanation

Returns

Type	Description
ModelEvaluation.Builder

setModelExplanation(ModelExplanation.Builder builderForValue)

public ModelEvaluation.Builder setModelExplanation(ModelExplanation.Builder builderForValue)

Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

.google.cloud.aiplatform.v1beta1.ModelExplanation model_explanation = 8;

Parameter

Name	Description
builderForValue	ModelExplanation.Builder

Returns

Type	Description
ModelEvaluation.Builder

setName(String value)

public ModelEvaluation.Builder setName(String value)

Output only. The resource name of the ModelEvaluation.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter

Name	Description
value	String The name to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setNameBytes(ByteString value)

public ModelEvaluation.Builder setNameBytes(ByteString value)

Output only. The resource name of the ModelEvaluation.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter

Name	Description
value	ByteString The bytes for name to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ModelEvaluation.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setSliceDimensions(int index, String value)

public ModelEvaluation.Builder setSliceDimensions(int index, String value)

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

repeated string slice_dimensions = 5;

Parameters

Name	Description
index	int The index to set the value at.
value	String The sliceDimensions to set.

Returns

Type	Description
ModelEvaluation.Builder	This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ModelEvaluation.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ModelEvaluation.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)