- 1.63.0 (latest)
- 1.62.0
- 1.60.0
- 1.59.0
- 1.58.0
- 1.57.0
- 1.56.0
- 1.55.0
- 1.54.1
- 1.53.0
- 1.52.0
- 1.51.0
- 1.50.0
- 1.49.0
- 1.48.0
- 1.47.0
- 1.46.0
- 1.45.0
- 1.44.0
- 1.43.0
- 1.39.0
- 1.38.1
- 1.37.0
- 1.36.4
- 1.35.0
- 1.34.0
- 1.33.1
- 1.32.0
- 1.31.1
- 1.30.1
- 1.29.0
- 1.28.1
- 1.27.1
- 1.26.1
- 1.25.0
- 1.24.1
- 1.23.0
- 1.22.1
- 1.21.0
- 1.20.0
- 1.19.1
- 1.18.3
- 1.17.1
- 1.16.1
- 1.15.1
- 1.14.0
- 1.13.1
- 1.12.1
- 1.11.0
- 1.10.0
- 1.9.0
- 1.8.1
- 1.7.1
- 1.6.2
- 1.5.0
- 1.4.3
- 1.3.0
- 1.2.0
- 1.1.1
- 1.0.1
- 0.9.0
- 0.8.0
- 0.7.1
- 0.6.0
- 0.5.1
- 0.4.0
- 0.3.1
ModelEvaluationSlice(mapping=None, *, ignore_unknown_fields=False, **kwargs)
A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.
Attributes |
|
---|---|
Name | Description |
name |
str
Output only. The resource name of the ModelEvaluationSlice. |
slice_ |
google.cloud.aiplatform_v1beta1.types.ModelEvaluationSlice.Slice
Output only. The slice of the test data that is used to evaluate the Model. |
metrics_schema_uri |
str
Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 `Schema Object |
metrics |
google.protobuf.struct_pb2.Value
Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri |
create_time |
google.protobuf.timestamp_pb2.Timestamp
Output only. Timestamp when this ModelEvaluationSlice was created. |
model_explanation |
google.cloud.aiplatform_v1beta1.types.ModelExplanation
Output only. 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 tabular Models. |
Classes
Slice
Slice(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Definition of a slice.
Methods
ModelEvaluationSlice
ModelEvaluationSlice(mapping=None, *, ignore_unknown_fields=False, **kwargs)
A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.