yat  0.16pre
Public Member Functions | List of all members
theplu::yat::classifier::SvmMultiClass Class Reference

Support Vector Machine for more than two classes. More...

#include <yat/classifier/SvmMultiClass.h>

Public Member Functions

 SvmMultiClass (void)
double C (void) const
 C-parameter. More...
SvmMultiClassmake_classifier (void) const
 Create an untrained copy of SvmMultiClass. More...
unsigned long int max_epochs (void) const
void max_epochs (unsigned long int)
 set maximal number of epochs in training
void predict (const KernelLookup &input, utility::Matrix &predict) const
 Generate prediction predict from input. More...
void set_C (double)
 set the C-Parameter
void train (const KernelLookup &kernel, const Target &target)
 Fit paramaters based on training data. More...

Detailed Description

Support Vector Machine for more than two classes.

New in yat 0.6

Member Function Documentation

double theplu::yat::classifier::SvmMultiClass::C ( void  ) const


See also
SvmMultiClass* theplu::yat::classifier::SvmMultiClass::make_classifier ( void  ) const

Create an untrained copy of SvmMultiClass.

A dynamically allocated SVM, which has to be deleted by the caller to avoid memory leaks.
unsigned long int theplu::yat::classifier::SvmMultiClass::max_epochs ( void  ) const

Default is max_epochs set to 100,000.

number of maximal epochs
void theplu::yat::classifier::SvmMultiClass::predict ( const KernelLookup input,
utility::Matrix predict 
) const

Generate prediction predict from input.

Each row in predict is calculated using a binary SVM.

inputkernel to base prediction on. Just like in SVM each column corresponds to a sample to predict, and each row corresponds to a training sample.
predictresulting predictions. Each column corresponds to a test sample (same as corresponding column in input). Row i corresponds to class i, in other words, a large value in row i suggests that test sample belongs to class i. If there were no training samples in class i, row i is filled with NaNs.
void theplu::yat::classifier::SvmMultiClass::train ( const KernelLookup kernel,
const Target target 

Fit paramaters based on training data.

For each class samples belonging to that class are trained against the other samples using a binary SVM.

kernelcontains the training data
targetinfomration on class labels

The documentation for this class was generated from the following file:

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