Class PerformanceMetrics

  • All Implemented Interfaces:
    Serializable, Cloneable

    public class PerformanceMetrics
    extends Object
    implements Serializable, Cloneable

    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.

    See Also:
    Serialized Form
    • Constructor Detail

      • PerformanceMetrics

        public PerformanceMetrics()
    • Method Detail

      • setProperties

        public void setProperties​(Map<String,​String> properties)
        Parameters:
        properties -
      • withProperties

        public PerformanceMetrics withProperties​(Map<String,​String> properties)
        Parameters:
        properties -
        Returns:
        Returns a reference to this object so that method calls can be chained together.
      • clearPropertiesEntries

        public PerformanceMetrics clearPropertiesEntries()
        Removes all the entries added into Properties. <p> Returns a reference to this object so that method calls can be chained together.
      • toString

        public String toString()
        Returns a string representation of this object; useful for testing and debugging.
        Overrides:
        toString in class Object
        Returns:
        A string representation of this object.
        See Also:
        Object.toString()
      • hashCode

        public int hashCode()
        Overrides:
        hashCode in class Object