Module Values.PerformanceMetricsSource

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.

Sourcetype nonrec t = {
  1. properties : PerformanceMetricsProperties.t option;
}
Sourceval make : ?properties:??? -> unit -> t
Sourceval to_value : t -> [> `Structure of (string * [> `Map of ([> `String of PerformanceMetricsPropertyKey.t ] * [> `String of PerformanceMetricsPropertyValue.t ]) list ]) list ]
Sourceval to_query : t -> Awso.Client.Query.t
Sourceval of_xml : Awso.Xml.t -> t
Sourceval of_string : string -> t
Sourceval of_json : Yojson.Safe.t -> t
Sourceval to_json : t -> Yojson.Safe.t