init(validationData:maxIterations:penalty:convergenceThreshold:featureRescaling:)
Creates a new set of parameters.
Declaration
init(validationData: MLDataTable?, maxIterations: Int = 11, penalty: Double = 1.0, convergenceThreshold: Double = 0.01, featureRescaling: Bool = true)Parameters
- validationData:
The dataset used to monitor how well the model is generalizing.
The default value is
nilwhich will use an automatically sampled validation set. - 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.