PerformanceMetrics class

Measurements of how well the MLModel performed on known observations. One of the following metrics is returned, based on the type of the MLModel:

  • BinaryAUC: The binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
  • RegressionRMSE: The regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.
  • MulticlassAvgFScore: The multiclass MLModel uses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
Annotations
  • @JsonSerializable(includeIfNull: false, explicitToJson: true, createFactory: true, createToJson: false)

Constructors

PerformanceMetrics({Map<String, String> properties})
PerformanceMetrics.fromJson(Map<String, dynamic> json)
factory

Properties

hashCode int
The hash code for this object. [...]
read-only, inherited
properties Map<String, String>
@JsonKey(name: 'Properties'), final
runtimeType Type
A representation of the runtime type of the object.
read-only, inherited

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a non-existent method or property is accessed. [...]
inherited
toString() String
A string representation of this object. [...]
inherited

Operators

operator ==(Object other) bool
The equality operator. [...]
inherited