ModelMonitoringSchema class final

The Model Monitoring Schema definition.

Inheritance
  • Object
  • ProtoMessage
  • ModelMonitoringSchema

Constructors

ModelMonitoringSchema({List<ModelMonitoringSchema_FieldSchema> featureFields = const [], List<ModelMonitoringSchema_FieldSchema> predictionFields = const [], List<ModelMonitoringSchema_FieldSchema> groundTruthFields = const []})
ModelMonitoringSchema.fromJson(Object? j)
factory

Properties

featureFields → List<ModelMonitoringSchema_FieldSchema>
Feature names of the model. Vertex AI will try to match the features from your dataset as follows:
final
groundTruthFields → List<ModelMonitoringSchema_FieldSchema>
Target /ground truth names of the model.
final
hashCode → int
The hash code for this object.
no setterinherited
predictionFields → List<ModelMonitoringSchema_FieldSchema>
Prediction output names of the model. The requirements are the same as the feature_fields. For AutoML Tables, the prediction output name presented in schema will be: predicted_{target_column}, the target_column is the one you specified when you train the model. For Prediction output drift analysis:
final
qualifiedName → String
The fully qualified name of this message, i.e., google.protobuf.Duration or google.rpc.ErrorInfo.
finalinherited
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toJson() → Object
override
toString() → String
A string representation of this object.
override

Operators

operator ==(Object other) → bool
The equality operator.
inherited

Constants

fullyQualifiedName → const String