Uses of Interface
org.jdmp.core.algorithm.regression.Regressor

Packages that use Regressor

Package	Description
org.jdmp.core.algorithm.classification
org.jdmp.core.algorithm.classification.bayes
org.jdmp.core.algorithm.classification.meta
org.jdmp.core.algorithm.classification.mlp
org.jdmp.core.algorithm.estimator
org.jdmp.core.algorithm.regression
org.jdmp.core.dataset

Uses of Regressor in org.jdmp.core.algorithm.classification

Subinterfaces of Regressor in org.jdmp.core.algorithm.classification

Modifier and Type	Interface and Description
interface	Classifier

Classes in org.jdmp.core.algorithm.classification that implement Regressor

Modifier and Type	Class and Description
class	AbstractClassifier
class	ConstantClassifier
class	KNNClassifier
class	RandomClassifier

Methods in org.jdmp.core.algorithm.classification that return Regressor

Modifier and Type	Method and Description
Regressor	KNNClassifier.emptyCopy()

Uses of Regressor in org.jdmp.core.algorithm.classification.bayes

Classes in org.jdmp.core.algorithm.classification.bayes that implement Regressor

Modifier and Type	Class and Description
class	NaiveBayesClassifier

Uses of Regressor in org.jdmp.core.algorithm.classification.meta

Classes in org.jdmp.core.algorithm.classification.meta that implement Regressor

Modifier and Type	Class and Description
class	Bagging
class	FeatureSelector
class	MultiClassClassifier
class	SemiSupervisedEM

Methods in org.jdmp.core.algorithm.classification.meta that return Regressor

Modifier and Type	Method and Description
Regressor	Bagging.emptyCopy()
Regressor	FeatureSelector.emptyCopy()
Regressor	SemiSupervisedEM.emptyCopy()

Constructors in org.jdmp.core.algorithm.classification.meta with parameters of type Regressor

Constructor and Description
Bagging(int bootstrapSize, Regressor... learningAlgorithms)
Bagging(Regressor... learningAlgorithms)
Bagging(Regressor learningAlgorithm, int count)
Bagging(Regressor learningAlgorithm, int count, int bootstrapSize)
FeatureSelector(FeatureSelector.SelectionType selectionType, Regressor learningAlgorithm, int featureCount)
SemiSupervisedEM(Regressor algorithm, ListDataSet unlabeledData, int iterations, boolean useRawPrediction)

Uses of Regressor in org.jdmp.core.algorithm.classification.mlp

Classes in org.jdmp.core.algorithm.classification.mlp that implement Regressor

Modifier and Type	Class and Description
class	MultiLayerNetwork

Uses of Regressor in org.jdmp.core.algorithm.estimator

Classes in org.jdmp.core.algorithm.estimator that implement Regressor

Modifier and Type	Class and Description
class	MultivariateGaussianDensityEstimator

Uses of Regressor in org.jdmp.core.algorithm.regression

Classes in org.jdmp.core.algorithm.regression that implement Regressor

Modifier and Type	Class and Description
class	AbstractRegressor
class	LinearRegression AlgorithmLinearRegression extends AlgorithmClassifier and not AlgorithmRegression because also classification is possible using regression
class	LinearRegressionGradientDescent
class	LogisticRegression

Methods in org.jdmp.core.algorithm.regression that return Regressor

Modifier and Type	Method and Description
Regressor	Regressor.emptyCopy()
Regressor	LinearRegression.emptyCopy()

Uses of Regressor in org.jdmp.core.dataset

Methods in org.jdmp.core.dataset with parameters of type Regressor

Modifier and Type	Method and Description
static ListMatrix<Double>	CrossValidation.run(Regressor algorithm, ListDataSet dataSet, int folds, int runs, long randomSeed)