class Google::Apis::PredictionV1_6::Insert2::ModelInfo
Model metadata.
Attributes
Estimated accuracy of model taking utility weights into account (Categorical models only). Corresponds to the JSON property `classWeightedAccuracy` @return [String]
A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an estimate, based on the amount and quality of the training data, of the estimated prediction accuracy. You can use this is a guide to decide whether the results are accurate enough for your needs. This estimate will be more reliable if your real input data is similar to your training data (Categorical models only) . Corresponds to the JSON property `classificationAccuracy` @return [String]
An estimated mean squared error. The can be used to measure the quality of the predicted model (Regression models only). Corresponds to the JSON property `meanSquaredError` @return [String]
Type of predictive model (CLASSIFICATION or REGRESSION). Corresponds to the JSON property `modelType` @return [String]
Number of valid data instances used in the trained model. Corresponds to the JSON property `numberInstances` @return [String]
Number of class labels in the trained model (Categorical models only). Corresponds to the JSON property `numberLabels` @return [String]
Public Class Methods
# File generated/google/apis/prediction_v1_6/classes.rb, line 597 def initialize(**args) update!(**args) end
Public Instance Methods
Update properties of this object
# File generated/google/apis/prediction_v1_6/classes.rb, line 602 def update!(**args) @class_weighted_accuracy = args[:class_weighted_accuracy] if args.key?(:class_weighted_accuracy) @classification_accuracy = args[:classification_accuracy] if args.key?(:classification_accuracy) @mean_squared_error = args[:mean_squared_error] if args.key?(:mean_squared_error) @model_type = args[:model_type] if args.key?(:model_type) @number_instances = args[:number_instances] if args.key?(:number_instances) @number_labels = args[:number_labels] if args.key?(:number_labels) end