Resource: ModelEvaluation
A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.
name 
 
  string 
 
Output only. The resource name of the ModelEvaluation.
displayName 
 
  string 
 
The display name of the ModelEvaluation.
metricsSchemaUri 
 
  string 
 
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 
.
metrics 
 
  value (  Value 
 
format) 
 
Evaluation metrics of the Model. The schema of the metrics is stored in  metricsSchemaUri 
 
createTime 
 
  string (  Timestamp 
 
format) 
 
Output only. timestamp when this ModelEvaluation was created.
Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" 
, "2014-10-02T15:01:23.045123456Z" 
or "2014-10-02T15:01:23+05:30" 
.
sliceDimensions[] 
 
  string 
 
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> 
.
dataItemSchemaUri 
 
  string 
 
Points to a YAML file stored on Google Cloud Storage describing [EvaluatedDataItemView.data_item_payload][] and  EvaluatedAnnotation.data_item_payload 
 
. The schema is defined as an OpenAPI 3.0.2 Schema Object 
.
This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.
annotationSchemaUri 
 
  string 
 
Points to a YAML file stored on Google Cloud Storage describing [EvaluatedDataItemView.predictions][], [EvaluatedDataItemView.ground_truths][],  EvaluatedAnnotation.predictions 
 
, and  EvaluatedAnnotation.ground_truths 
 
. The schema is defined as an OpenAPI 3.0.2 Schema Object 
.
This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.
modelExplanation 
 
  object (  ModelExplanation 
 
) 
 
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.
explanationSpecs[] 
 
  object (  ModelEvaluationExplanationSpec 
 
) 
 
Describes the values of  ExplanationSpec 
 
that are used for explaining the predicted values on the evaluated data.
| JSON representation | 
|---|
| { "name" : string , "displayName" : string , "metricsSchemaUri" : string , "metrics" : value , "createTime" : string , "sliceDimensions" : [ string ] , "dataItemSchemaUri" : string , "annotationSchemaUri" : string , "modelExplanation" : { object ( | 
ModelEvaluationExplanationSpec
explanationType 
 
  string 
 
Explanation type.
For AutoML Image Classification models, possible values are:
-  image-integrated-gradients
-  image-xrai
explanationSpec 
 
  object (  ExplanationSpec 
 
) 
 
Explanation spec details.
| JSON representation | 
|---|
|  { 
 "explanationType" 
 : 
 string 
 , 
 "explanationSpec" 
 : 
 { 
 object (  | 
| Methods | |
|---|---|
|   | Gets a ModelEvaluation. | 
|   | Imports an externally generated ModelEvaluation. | 
|   | Lists ModelEvaluations in a Model. | 

