init(validation:maxIterations:penalty:convergenceThreshold:featureRescaling:)
Creates a new set of parameters.
Declaration
init(validation: MLSupportVectorClassifier.ModelParameters.ValidationData = .split(strategy: .automatic), maxIterations: Int = 11, penalty: Double = 1.0, convergenceThreshold: Double = 0.01, featureRescaling: Bool = true)Parameters
- validation:
The data used to monitor how well the model is generalizing.
The default is to automatically split off some data from the training set for validation.
- maxIterations:
The maximum number of passes through the data.
The default value is 11.
- penalty:
Weight of the regularizer. The larger the penalty the less variance in the model.
The default value is 1.0.
- convergenceThreshold:
The threshold with which to determine if the model has converged. Consider reducing this value for higher training accuracy, but beware of overfitting.
The default value is 0.01.
- featureRescaling:
Determines if the features should be preprocessed to ensure all features are on the same scale.
The default value is true.