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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.BuilderImplements
ModelEvaluationOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
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;
Name | Description |
values | Iterable<? extends com.google.cloud.aiplatform.v1beta1.ModelEvaluation.ModelEvaluationExplanationSpec> |
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;
Name | Description |
values | Iterable<String> The sliceDimensions to add. |
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;
Name | Description |
value | ModelEvaluation.ModelEvaluationExplanationSpec |
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;
Name | Description |
builderForValue | ModelEvaluation.ModelEvaluationExplanationSpec.Builder |
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;
Name | Description |
index | int |
value | ModelEvaluation.ModelEvaluationExplanationSpec |
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;
Name | Description |
index | int |
builderForValue | ModelEvaluation.ModelEvaluationExplanationSpec.Builder |
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;
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;
Name | Description |
index | int |
Type | Description |
ModelEvaluation.ModelEvaluationExplanationSpec.Builder |
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public ModelEvaluation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
ModelEvaluation.Builder |
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;
Name | Description |
value | String The sliceDimensions to add. |
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;
Name | Description |
value | ByteString The bytes of the sliceDimensions to add. |
Type | Description |
ModelEvaluation.Builder | This builder for chaining. |
build()
public ModelEvaluation build()
Type | Description |
ModelEvaluation |
buildPartial()
public ModelEvaluation buildPartial()
Type | Description |
ModelEvaluation |
clear()
public ModelEvaluation.Builder clear()
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];
Type | Description |
ModelEvaluation.Builder |
clearDisplayName()
public ModelEvaluation.Builder clearDisplayName()
The display name of the ModelEvaluation.
string display_name = 10;
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;
Type | Description |
ModelEvaluation.Builder |
clearField(Descriptors.FieldDescriptor field)
public ModelEvaluation.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
ModelEvaluation.Builder |
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;
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;
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;
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;
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];
Type | Description |
ModelEvaluation.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public ModelEvaluation.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
ModelEvaluation.Builder |
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;
Type | Description |
ModelEvaluation.Builder | This builder for chaining. |
clone()
public ModelEvaluation.Builder clone()
Type | Description |
ModelEvaluation.Builder |
getCreateTime()
public Timestamp getCreateTime()
Output only. Timestamp when this ModelEvaluation was created.
.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
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];
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];
Type | Description |
TimestampOrBuilder |
getDefaultInstanceForType()
public ModelEvaluation getDefaultInstanceForType()
Type | Description |
ModelEvaluation |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
getDisplayName()
public String getDisplayName()
The display name of the ModelEvaluation.
string display_name = 10;
Type | Description |
String | The displayName. |
getDisplayNameBytes()
public ByteString getDisplayNameBytes()
The display name of the ModelEvaluation.
string display_name = 10;
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;
Name | Description |
index | int |
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;
Name | Description |
index | int |
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;
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;
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;
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;
Name | Description |
index | int |
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;
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;
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;
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;
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;
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;
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;
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;
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;
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;
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;
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;
Type | Description |
ModelExplanationOrBuilder |
getName()
public String getName()
Output only. The resource name of the ModelEvaluation.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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];
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;
Name | Description |
index | int The index of the element to return. |
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;
Name | Description |
index | int The index of the value to return. |
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;
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;
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];
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;
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;
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;
Type | Description |
boolean | Whether the modelExplanation field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
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];
Name | Description |
value | Timestamp |
Type | Description |
ModelEvaluation.Builder |
mergeFrom(ModelEvaluation other)
public ModelEvaluation.Builder mergeFrom(ModelEvaluation other)
Name | Description |
other | ModelEvaluation |
Type | Description |
ModelEvaluation.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public ModelEvaluation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelEvaluation.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public ModelEvaluation.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
ModelEvaluation.Builder |
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;
Name | Description |
value | Value |
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;
Name | Description |
value | Value |
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;
Name | Description |
value | ModelExplanation |
Type | Description |
ModelEvaluation.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final ModelEvaluation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
ModelEvaluation.Builder |
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;
Name | Description |
index | int |
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];
Name | Description |
value | Timestamp |
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];
Name | Description |
builderForValue | Builder |
Type | Description |
ModelEvaluation.Builder |
setDisplayName(String value)
public ModelEvaluation.Builder setDisplayName(String value)
The display name of the ModelEvaluation.
string display_name = 10;
Name | Description |
value | String The displayName to set. |
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;
Name | Description |
value | ByteString The bytes for displayName to set. |
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;
Name | Description |
index | int |
value | ModelEvaluation.ModelEvaluationExplanationSpec |
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;
Name | Description |
index | int |
builderForValue | ModelEvaluation.ModelEvaluationExplanationSpec.Builder |
Type | Description |
ModelEvaluation.Builder |
setField(Descriptors.FieldDescriptor field, Object value)
public ModelEvaluation.Builder setField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
ModelEvaluation.Builder |
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;
Name | Description |
value | Value |
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;
Name | Description |
builderForValue | Builder |
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;
Name | Description |
value | Value |
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;
Name | Description |
builderForValue | Builder |
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;
Name | Description |
value | String The metricsSchemaUri to set. |
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;
Name | Description |
value | ByteString The bytes for metricsSchemaUri to set. |
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;
Name | Description |
value | ModelExplanation |
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;
Name | Description |
builderForValue | ModelExplanation.Builder |
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];
Name | Description |
value | String The name to set. |
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];
Name | Description |
value | ByteString The bytes for name to set. |
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)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
ModelEvaluation.Builder |
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;
Name | Description |
index | int The index to set the value at. |
value | String The sliceDimensions to set. |
Type | Description |
ModelEvaluation.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final ModelEvaluation.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
ModelEvaluation.Builder |