Nu-Support Vector Machine for classification. More...

#include <nusvc.h>

Inheritance diagram for NuSVC:

Protected Member Functions
void	train_binary (const DataSet &dataset, int i, int j, SyncArray< float_type > &alpha, float_type &rho) override

Protected Member Functions inherited from SVC
void	model_setup (const DataSet &dataset, SvmParam &param) override

Additional Inherited Members
Public Member Functions inherited from SVC
void	train (const DataSet &dataset, SvmParam param) override

vector< float_type >	predict (const DataSet::node2d &instances, int batch_size) override

Public Member Functions inherited from SvmModel
void	predict_dec_values (const DataSet::node2d &instances, SyncArray< float_type > &dec_values, int batch_size) const

virtual vector< float_type >	cross_validation (DataSet dataset, SvmParam param, int n_fold)

virtual void	save_to_file (string path)

virtual void	load_from_file (string path)

Protected Attributes inherited from SvmModel
SvmParam	param

SyncArray< float_type >	coef

DataSet::node2d	sv

SyncArray< int >	n_sv
	the number of support vectors for each class

int	n_total_sv
	the number of support vectors for all classes

SyncArray< float_type >	rho
	the bias term for each binary model

int	n_classes = 2
	the number of classes

size_t	n_binary_models
	the number of binary models, equal to \(k(k-1)/2\), where \(k\) is the number of classes

vector< float_type >	probA
	be used to predict probability for each binary model

vector< float_type >	probB
	be used to predict probability for each binary model

vector< int >	label
	only for SVC, maps logical label (0,1,2,...) to real label in dataset (maybe 2,4,5,...)

Detailed Description

Nu-Support Vector Machine for classification.

Member Function Documentation

overrideprotectedvirtual

train a binary SVC model \(SVM_{i,j}\) for class i and class j.

Parameters

[in]	dataset	original dataset
[in]	i
[in]	j
[out]	alpha	optimization variables \(\boldsymbol{\alpha}\) in dual problem, should be initialized with the same size of the number of instances in this binary problem
[out]	rho	bias term \(b\) in dual problem

Reimplemented from SVC.

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