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LSSVMFactory Class Reference

The class serves as a kind of base class for LS-SVM based modelers, it takes care of parsing and holding the basic configuration options that any LSSVM modeler needs. More...

Inheritance diagram for LSSVMFactory:
Inheritance graph
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Public Member Functions

function LSSVMFactory (var varargin)
 Class constructor. More...
 
function getModelType ()
 TODO. More...
 
function getObservables ()
 TODO. More...
 
function getType ()
 TODO. More...
 
function getBackend ()
 TODO. More...
 
function getKernel ()
 TODO. More...
 
function supportsComplexData ()
 TODO. More...
 
function supportsMultipleOutputs ()
 TODO. More...
 
function getBounds ()
 TODO. More...
 
function createInitialModels (var number, var wantModels)
 TODO. More...
 
function createModel (var parameters)
 TODO. More...
 
function createRandomModel ()
 TODO. More...
 
function mutation (var parents, var options, var nvars, var FitnessFcn, var state, var thisScore, var thisPopulation)
 TODO. More...
 
function crossover (var parents, var options, var nvars, var FitnessFcn, var unused, var thisPopulation)
 TODO. More...
 
function getConstraintFcn ()
 TODO. More...
 
function getCreationFcn ()
 TODO. More...
 
function getCrossoverFcn ()
 TODO. More...
 
function getMutationFcn ()
 TODO. More...
 
function isCustomMode ()
 TODO. More...
 
function getBatchObservables ()
 TODO. More...
 
function getIndividualSize ()
 TODO. More...
 
function setSamples (var samples, var values)
 TODO. More...
 
function getIntegerParameters ()
 MATLAB GA supports handling parameters as integers, override this function in derived factories when parameters must be handled as integers. More...
 
function getBasicBatchObservables ()
 TODO. More...
 
function createInitialPopulation (var GenomeLength, var FitnessFcn, var options)
 TODO. More...
 
function wrapFunctions ()
 TODO. More...
 
function getSamples ()
 TODO. More...
 
function getDimensions ()
 TODO. More...
 
function getParallelMode ()
 TODO. More...
 
function getMode ()
 TODO. More...
 

Protected Member Functions

function genModel (var params)
 Given a set of model parameters, return the real models (untrained) More...
 

Protected Attributes

var type
 
var kernel
 
var kernelParamBounds
 
var regParamBounds
 
var nu
 
var epsilon
 
var stoppingTolerance
 
var probabilistic
 
var extraParams
 

Detailed Description

The class serves as a kind of base class for LS-SVM based modelers, it takes care of parsing and holding the basic configuration options that any LSSVM modeler needs.

Constructor & Destructor Documentation

function LSSVMFactory ( var  varargin)
inline

Class constructor.

Returns
instance of the class

Member Function Documentation

function createInitialModels ( var  number,
var  wantModels 
)
inherited

TODO.

Return 'number' individuals.

If wantModels is false only return a parameter matrix where each row uniquely represents one model. If wantModels is true a row vector model objects is returned.

function createInitialPopulation ( var  GenomeLength,
var  FitnessFcn,
var  options 
)
inherited

TODO.

A function that creates an initial population.

The input arguments to the function are Genomelength : Number of independent variables for the fitness function FitnessFcn : Fitness function options : Options structure The function returns Population, the initial population for the genetic algorithm.

function createModel ( var  parameters)
inherited

TODO.

Given an individual representing a model, return a real model.

function createRandomModel ( )
inherited

TODO.

Return a randomly chosen SVM model.

function crossover ( var  parents,
var  options,
var  nvars,
var  FitnessFcn,
var  unused,
var  thisPopulation 
)
inherited

TODO.

A Simple crossover operator The arguments to the function are.

  • parents — Row vector of parents chosen by the selection function
  • options — options structure
  • nvars — Number of variables
  • FitnessFcn — Fitness function
  • unused — Placeholder not used
  • thisPopulation — Matrix representing the current population. The number of rows of the matrix is Population size and the number of columns is Number of variables.
function genModel ( var  params)
protected

Given a set of model parameters, return the real models (untrained)

function getBackend ( )
inlineinherited

TODO.

function getBasicBatchObservables ( )
inherited

TODO.

Generate the observable objects that handle grouped data.

function getBatchObservables ( )
inlineinherited

TODO.

function getBounds ( )
inlineinherited

TODO.

function getConstraintFcn ( )
inlineinherited

TODO.

function getCreationFcn ( )
inlineinherited

TODO.

function getCrossoverFcn ( )
inlineinherited

TODO.

function getDimensions ( )
inlineinherited

TODO.

function getIndividualSize ( )
inlineinherited

TODO.

function getIntegerParameters ( )
inlineinherited

MATLAB GA supports handling parameters as integers, override this function in derived factories when parameters must be handled as integers.

function getKernel ( )
inlineinherited

TODO.

function getMode ( )
inlineinherited

TODO.

function getModelType ( )
inline

TODO.

function getMutationFcn ( )
inlineinherited

TODO.

function getObservables ( )

TODO.

Returns observables.

function getParallelMode ( )
inlineinherited

TODO.

function getSamples ( )
inlineinherited

TODO.

function getType ( )
inlineinherited

TODO.

function isCustomMode ( )
inlineinherited

TODO.

function mutation ( var  parents,
var  options,
var  nvars,
var  FitnessFcn,
var  state,
var  thisScore,
var  thisPopulation 
)
inherited

TODO.

Simple mutation operator that wraps mutateSVM The arguments to the function are.

  • parents : Row vector of parents chosen by the selection function
  • options : Options structure
  • nvars : Number of variables
  • FitnessFcn : Fitness function
  • state : Structure containing information about the current generation.
  • thisScore : Vector of scores of the current population
  • thisPopulation : Matrix of individuals in the current population

The function returns mutationChildren — the mutated offspring — as a matrix whose rows correspond to the children. The number of columns of the matrix is Number of variables.

function setSamples ( var  samples,
var  values 
)
inlineinherited

TODO.

function supportsComplexData ( )
inlineinherited

TODO.

function supportsMultipleOutputs ( )
inlineinherited

TODO.

function wrapFunctions ( )
inherited

TODO.

Create anonymous function handles to wrap all operator functions to members of the given obj The genetic operator functions are memberfunctions and thus need to be called with the 'this' object (s).

To make this possible we need to wrap them in an anonymous function. And set them again as function handles.

Member Data Documentation

var epsilon
protectedinherited
var extraParams
protectedinherited
var kernel
protectedinherited
var kernelParamBounds
protectedinherited
var nu
protectedinherited
var probabilistic
protectedinherited
var regParamBounds
protectedinherited
var stoppingTolerance
protectedinherited
var type
protectedinherited

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