public final class ModelEvaluation extends GeneratedMessageV3 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
Static Fields
public static final int CREATE_TIME_FIELD_NUMBER
Field Value
public static final int DISPLAY_NAME_FIELD_NUMBER
Field Value
public static final int EXPLANATION_SPECS_FIELD_NUMBER
Field Value
public static final int METADATA_FIELD_NUMBER
Field Value
public static final int METRICS_FIELD_NUMBER
Field Value
public static final int METRICS_SCHEMA_URI_FIELD_NUMBER
Field Value
public static final int MODEL_EXPLANATION_FIELD_NUMBER
Field Value
public static final int NAME_FIELD_NUMBER
Field Value
public static final int SLICE_DIMENSIONS_FIELD_NUMBER
Field Value
Static Methods
public static ModelEvaluation getDefaultInstance()
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public static final Descriptors.Descriptor getDescriptor()
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public static ModelEvaluation.Builder newBuilder()
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public static ModelEvaluation.Builder newBuilder(ModelEvaluation prototype)
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public static ModelEvaluation parseDelimitedFrom(InputStream input)
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public static ModelEvaluation parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static ModelEvaluation parseFrom(byte[] data)
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Name | Description |
data | byte[]
|
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public static ModelEvaluation parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
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public static ModelEvaluation parseFrom(ByteString data)
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public static ModelEvaluation parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
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public static ModelEvaluation parseFrom(CodedInputStream input)
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public static ModelEvaluation parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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public static ModelEvaluation parseFrom(InputStream input)
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public static ModelEvaluation parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static ModelEvaluation parseFrom(ByteBuffer data)
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public static ModelEvaluation parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
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public static Parser<ModelEvaluation> parser()
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Methods
public boolean equals(Object obj)
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Overrides
public Timestamp getCreateTime()
Output only. Timestamp when this ModelEvaluation was created.
.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
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public TimestampOrBuilder getCreateTimeOrBuilder()
Output only. Timestamp when this ModelEvaluation was created.
.google.protobuf.Timestamp create_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
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public ModelEvaluation getDefaultInstanceForType()
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public String getDisplayName()
The display name of the ModelEvaluation.
string display_name = 10;
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Type | Description |
String | The displayName.
|
public ByteString getDisplayNameBytes()
The display name of the ModelEvaluation.
string display_name = 10;
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Type | Description |
ByteString | The bytes for displayName.
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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;
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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;
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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;
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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;
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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> | |
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.
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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
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.
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public ValueOrBuilder getMetricsOrBuilder()
Evaluation metrics of the Model. The schema of the metrics is stored in
metrics_schema_uri
.google.protobuf.Value metrics = 3;
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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.
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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.
|
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
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
Output only. The resource name of the ModelEvaluation.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns
Type | Description |
String | The name.
|
public ByteString getNameBytes()
Output only. The resource name of the ModelEvaluation.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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public Parser<ModelEvaluation> getParserForType()
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Overrides
public int getSerializedSize()
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Overrides
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.
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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.
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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.
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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;
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public final UnknownFieldSet getUnknownFields()
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Overrides
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.
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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.
|
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.
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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.
|
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Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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public final boolean isInitialized()
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public ModelEvaluation.Builder newBuilderForType()
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protected ModelEvaluation.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
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protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
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public ModelEvaluation.Builder toBuilder()
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public void writeTo(CodedOutputStream output)
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Exceptions