Package gov.nih.mipav.model.algorithms

Class SVM.VlSvm

java.lang.Object

gov.nih.mipav.model.algorithms.SVM.VlSvm

Enclosing class:

SVM

public class SVM.VlSvm
extends java.lang.Object

Field Summary

Fields

Modifier and Type	Field	Description
(package private) int	accumulateFn
(package private) double[]	alpha	< Bias learning rate.
(package private) double	bias	< Model ($\bw$ vector).
(package private) double	biasLearningRate
(package private) double	biasMultiplier	< Bias.
(package private) int	conjugateLossFn
(package private) SVM.VlSvmDataset	data	< Regularizer multiplier.
(package private) int	dcaUpdateFn
(package private) int	diagnosticFn	< Optional owned dataset.
(package private) double[]	diagnosticFnData
(package private) int	diagnosticFrequency
(package private) int	dimension	< SVM solver type.
(package private) double	epsilon	< Maximum number of iterations.
(package private) int	innerProductFn
(package private) int	iteration
(package private) double[]	labels
(package private) double	lambda	< Bias feature multiplier.
(package private) int	lossDerivativeFn
(package private) int	lossFn	< Frequency of diagnostic.
(package private) int	maxNumIterations	< Current iterations number.
(package private) double[]	model	< Model dimension.
(package private) int	numData
(package private) SVM.VlSvmDataset	ownDataset	< Data weights.
(package private) double[]	scores	< Statistcs.
(package private) SVM.VlSvmSolverType	solver
(package private) SVM.VlSvmStatistics	statistics	< Stopping threshold.
(package private) double[]	weights	< Data labels.

Constructor Summary

Constructors

Constructor	Description
VlSvm()

Method Summary

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

solver

SVM.VlSvmSolverType solver

dimension

int dimension

< SVM solver type.

model

double[] model

< Model dimension.

bias

double bias

< Model ($\bw$ vector).

biasMultiplier

double biasMultiplier

< Bias.

lambda

double lambda

< Bias feature multiplier.

data

SVM.VlSvmDataset data

< Regularizer multiplier.

numData

int numData

labels

double[] labels

weights

double[] weights

< Data labels.

ownDataset

SVM.VlSvmDataset ownDataset

< Data weights.

diagnosticFn

int diagnosticFn

< Optional owned dataset.

diagnosticFnData

double[] diagnosticFnData

diagnosticFrequency

int diagnosticFrequency

lossFn

int lossFn

< Frequency of diagnostic.

conjugateLossFn

int conjugateLossFn

lossDerivativeFn

int lossDerivativeFn

dcaUpdateFn

int dcaUpdateFn

innerProductFn

int innerProductFn

accumulateFn

int accumulateFn

iteration

int iteration

maxNumIterations

int maxNumIterations

< Current iterations number.

epsilon

double epsilon

< Maximum number of iterations.

statistics

SVM.VlSvmStatistics statistics

< Stopping threshold.

scores

double[] scores

< Statistcs.

biasLearningRate

double biasLearningRate

alpha

double[] alpha

< Bias learning rate.

Constructor Detail

VlSvm

public VlSvm()