org.jdmp.core.algorithm.regression

Interface Regressor

All Known Subinterfaces:

Classifier

All Known Implementing Classes:

AbstractClassifier, AbstractRegressor, Bagging, ConstantClassifier, FeatureSelector, KNNClassifier, LinearRegression, LinearRegressionGradientDescent, LogisticRegression, MultiClassClassifier, MultiLayerNetwork, MultivariateGaussianDensityEstimator, NaiveBayesClassifier, RandomClassifier, SemiSupervisedEM

public interface Regressor

Method Summary

Modifier and Type	Method and Description
Regressor	emptyCopy()
int	getClassCount(ListDataSet dataSet)
int	getFeatureCount(ListDataSet dataSet)
java.lang.String	getInputLabel()
java.lang.String	getTargetLabel()
boolean	isDiscrete(ListDataSet dataSet)
void	predictAll(ListDataSet dataSet)
Matrix	predictOne(Matrix input)
void	predictOne(Sample sample)
void	reset()
void	trainAll(ListDataSet dataSet)
void	trainOne(Matrix input, Matrix target)
void	trainOne(Matrix input, Matrix sampleWeight, Matrix target)
void	trainOne(Sample sample)

Method Detail

trainAll

void trainAll(ListDataSet dataSet)

reset

void reset()

trainOne

void trainOne(Matrix input,
              Matrix sampleWeight,
              Matrix target)

predictOne

void predictOne(Sample sample)

predictOne

Matrix predictOne(Matrix input)

trainOne

void trainOne(Matrix input,
              Matrix target)

trainOne

void trainOne(Sample sample)

predictAll

void predictAll(ListDataSet dataSet)

emptyCopy

Regressor emptyCopy()

getInputLabel

java.lang.String getInputLabel()

getTargetLabel

java.lang.String getTargetLabel()

getClassCount

int getClassCount(ListDataSet dataSet)

getFeatureCount

int getFeatureCount(ListDataSet dataSet)

isDiscrete

boolean isDiscrete(ListDataSet dataSet)