The SVMTrain analyzer creates a SVM model for the given dataset using libsvm. More...

#include <svmtrain.h>

Inheritance diagram for gaia2::SVMTrain:

Public Member Functions
	SVMTrain (const ParameterMap &params)

Transformation	analyze (const DataSet *data) const

Public Member Functions inherited from gaia2::Analyzer
	Analyzer (const ParameterMap &params)

virtual Transformation	analyze (const DataSet *dataset, const Region &region) const

void	checkDataSet (const DataSet *dataset) const
	Checks that the given dataset is valid. More...

void	checkMinPoints (const DataSet *dataset, int n) const
	Checks that the given dataset as at least the specified number of points. More...

const Region &	checkFixedLength (const Region &region, const PointLayout &layout) const
	Checks that the given Region only contains fixed-length descriptors and throws an exception if not. More...

Static Protected Member Functions
static void	initParams ()
	Fills params translation maps, etc...

Protected Attributes
QString	_className

Protected Attributes inherited from gaia2::Analyzer
ParameterMap	_params

QStringList	_descriptorNames

QStringList	_exclude

Static Protected Attributes
static bool	_paramsInitialized = false

static GaiaMap< QString, int, GaiaException >	_svmTypeMap

static GaiaMap< QString, int, GaiaException >	_kernelTypeMap

Additional Inherited Members
Public Attributes inherited from gaia2::Analyzer
QString	name
	Name for the algorithm, usually the key that was used to instantiate it from the factory.

QStringList	validParams
	List of valid parameters this analyzer accepts. More...

Detailed Description

The SVMTrain analyzer creates a SVM model for the given dataset using libsvm.

Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.

Parameters

className	the name of the descriptor which is to be used as the class
type	the SVM type. Available types are: C-SVC nu-SVC one-class epsilon-SVR nu-SVR (default: C-SVC)
kernel	the kernel type. Available types are: linear polynomial (poly) radial (basis function) (also called RBF) sigmoid (default: RBF)
probability	whether to train the model for probability estimates (default: false)
degree	the degree in the kernel function (default 3)
c	the cost parameter `C` used in C-SVC, epsilon-SVR, and nu-SVR (default 1)
nu	the `nu` parameter of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
gamma	the `gamma` coeff in the kernel function (default 1/dim)

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

Public Member Functions