- Type Parameters:
InputType - The type of input data in the input-output pair that
the learner can learn from. The Evaluator learned from the
algorithm also takes this as the input parameter.EvaluatorType - The type of object created by the learning algorithm.
- All Superinterfaces:
- BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,Vectorizable>>,EvaluatorType>, java.lang.Cloneable, CloneableSerializable, Regression<InputType,Vectorizable,EvaluatorType>, java.io.Serializable, SupervisedBatchLearner<InputType,Vectorizable,EvaluatorType>
@PublicationReference(author="Wikipedia",
title="General linear model",
type=WebPage,
year=2012,
url="http://en.wikipedia.org/wiki/Multivariate_regression",
notes={"The only article on Multivariate Regression I could find only talks about the linear case.","This interface, however, can deal with the nonlinear case as well."})
public interface MultivariateRegression<InputType,EvaluatorType extends Evaluator<? super InputType,? extends Vectorizable>>
extends Regression<InputType,Vectorizable,EvaluatorType>
A regression algorithm that maps one or more independent (input) variables
onto multiple output variables.
- Since:
- 3.4.2
- Author:
- Kevin R. Dixon