C# 클래스 Encog.ML.SVM.SupportVectorMachine

상속: Encog.ML.BasicML, IMLMethod, IMLRegression, IMLInputOutput, IMLInput, IMLOutput, IMLClassification, IMLError
파일 보기 프로젝트 열기: encog/encog-silverlight-core 1 사용 예제들

공개 메소드들

메소드 설명
CalculateError ( IMLDataSet data ) : double

Calculate the error for this SVM.

Classify ( IMLData input ) : int
Compute ( IMLData input ) : IMLData

Compute the output for the given input.

MakeSparse ( IMLData data ) : Encog.MathUtil.LIBSVM.svm_node[]

Convert regular Encog MLData into the "sparse" data needed by an SVM.

SupportVectorMachine ( ) : System

Construct the SVM.

SupportVectorMachine ( int theInputCount, SVMType svmType, KernelType kernelType ) : System

Construct a SVM network.

SupportVectorMachine ( int theInputCount, bool regression ) : System

Construct an SVM network. For regression it will use an epsilon support vector. Both types will use an RBF kernel.

SupportVectorMachine ( svm_model theModel ) : System

Construct a SVM from a model.

UpdateProperties ( ) : void

Not needed, no properties to update.

메소드 상세

CalculateError() 공개 메소드

Calculate the error for this SVM.
public CalculateError ( IMLDataSet data ) : double
data IMLDataSet The training set.
리턴 double

Classify() 공개 메소드

public Classify ( IMLData input ) : int
input IMLData
리턴 int

Compute() 공개 메소드

Compute the output for the given input.
public Compute ( IMLData input ) : IMLData
input IMLData The input to the SVM.
리턴 IMLData

MakeSparse() 공개 메소드

Convert regular Encog MLData into the "sparse" data needed by an SVM.
public MakeSparse ( IMLData data ) : Encog.MathUtil.LIBSVM.svm_node[]
data IMLData The data to convert.
리턴 Encog.MathUtil.LIBSVM.svm_node[]

SupportVectorMachine() 공개 메소드

Construct the SVM.
public SupportVectorMachine ( ) : System
리턴 System

SupportVectorMachine() 공개 메소드

Construct a SVM network.
public SupportVectorMachine ( int theInputCount, SVMType svmType, KernelType kernelType ) : System
theInputCount int The input count.
svmType SVMType The type of SVM.
kernelType KernelType The SVM kernal type.
리턴 System

SupportVectorMachine() 공개 메소드

Construct an SVM network. For regression it will use an epsilon support vector. Both types will use an RBF kernel.
public SupportVectorMachine ( int theInputCount, bool regression ) : System
theInputCount int The input count.
regression bool True if this network is used for regression.
리턴 System

SupportVectorMachine() 공개 메소드

Construct a SVM from a model.
public SupportVectorMachine ( svm_model theModel ) : System
theModel Encog.MathUtil.LIBSVM.svm_model The model.
리턴 System

UpdateProperties() 공개 메소드

Not needed, no properties to update.
public UpdateProperties ( ) : void
리턴 void