Class ModelEvaluation.Builder (3.42.0) 

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

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

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

clearBiasConfigs()

public ModelEvaluation.Builder clearBiasConfigs()

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Returns
Type Description
ModelEvaluation.Builder

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

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", "row_based_metrics_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

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

getBiasConfigs()

public ModelEvaluation.BiasConfig getBiasConfigs()

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Returns
Type Description
ModelEvaluation.BiasConfig

The biasConfigs.

getBiasConfigsBuilder()

public ModelEvaluation.BiasConfig.Builder getBiasConfigsBuilder()

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Returns
Type Description
ModelEvaluation.BiasConfig.Builder

getBiasConfigsOrBuilder()

public ModelEvaluation.BiasConfigOrBuilder getBiasConfigsOrBuilder()

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Returns
Type Description
ModelEvaluation.BiasConfigOrBuilder

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

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", "row_based_metrics_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", "row_based_metrics_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", "row_based_metrics_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.

hasBiasConfigs()

public boolean hasBiasConfigs()

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Returns
Type Description
boolean

Whether the biasConfigs field is set.

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", "row_based_metrics_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

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeBiasConfigs(ModelEvaluation.BiasConfig value)

public ModelEvaluation.Builder mergeBiasConfigs(ModelEvaluation.BiasConfig value)

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Parameter
Name Description
value ModelEvaluation.BiasConfig
Returns
Type Description
ModelEvaluation.Builder

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
Exceptions
Type Description
IOException

mergeFrom(Message other)

public ModelEvaluation.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
ModelEvaluation.Builder
Overrides

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", "row_based_metrics_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

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

setBiasConfigs(ModelEvaluation.BiasConfig value)

public ModelEvaluation.Builder setBiasConfigs(ModelEvaluation.BiasConfig value)

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Parameter
Name Description
value ModelEvaluation.BiasConfig
Returns
Type Description
ModelEvaluation.Builder

setBiasConfigs(ModelEvaluation.BiasConfig.Builder builderForValue)

public ModelEvaluation.Builder setBiasConfigs(ModelEvaluation.BiasConfig.Builder builderForValue)

Specify the configuration for bias detection.

.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig bias_configs = 12;

Parameter
Name Description
builderForValue ModelEvaluation.BiasConfig.Builder
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

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", "row_based_metrics_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", "row_based_metrics_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

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