Interface ModelEvaluationOrBuilder (3.35.0)

Version 3.35.0

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public interface ModelEvaluationOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getBiasConfigs()

public abstract 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.

getBiasConfigsOrBuilder()

public abstract 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 abstract 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.

getCreateTimeOrBuilder()

public abstract 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

getDisplayName()

public abstract String getDisplayName()

The display name of the ModelEvaluation.

string display_name = 10;

Returns
Type	Description
String	The displayName.

getDisplayNameBytes()

public abstract ByteString getDisplayNameBytes()

The display name of the ModelEvaluation.

string display_name = 10;

Returns
Type	Description
ByteString	The bytes for displayName.

getExplanationSpecs(int index)

public abstract 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

getExplanationSpecsCount()

public abstract 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 abstract 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 abstract 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 abstract 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 abstract 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.

getMetadataOrBuilder()

public abstract 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 abstract 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.

getMetricsOrBuilder()

public abstract 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 abstract 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 abstract 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 abstract 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.

getModelExplanationOrBuilder()

public abstract 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 abstract 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 abstract 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 abstract 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 abstract 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 abstract 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 abstract List<String> 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
List<String>	A list containing the sliceDimensions.

hasBiasConfigs()

public abstract 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 abstract 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 abstract 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 abstract 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 abstract 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.