- 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.OutputType - The type of output data in the input-output pair that
the learner can learn from. The Evaluator learned from the
algorithm also produces this as its output.EvaluatorType - The type of object created by the learning algorithm.
For example, a FeedforwardNeuralNetwork.
- All Superinterfaces:
- BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,EvaluatorType>, java.lang.Cloneable, CloneableSerializable, java.io.Serializable, SupervisedBatchLearner<InputType,OutputType,EvaluatorType>
- All Known Subinterfaces:
- MultivariateRegression<InputType,EvaluatorType>, UnivariateRegression<InputType,EvaluatorType>
@PublicationReference(author="Wikipedia",
title="Regression Analysis",
type=WebPage,
url="http://en.wikipedia.org/wiki/Regression_analysis",
year=2012)
public interface Regression<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>
extends SupervisedBatchLearner<InputType,OutputType,EvaluatorType>
A supervised learning algorithm that attempts to interpolate/extrapolate
inputs given a training set of input/output pairs.
- Since:
- 3.4.2
- Author:
- Kevin R. Dixon