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SVMFactory Class Reference

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

Inheritance diagram for SVMFactory:
Inheritance graph
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Public Member Functions

function SVMFactory (var varargin)
 Class constructor. 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 getObservables ()
 TODO. More...
 
function getModelType ()
 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 SVM based modelers, it takes care of parsing and holding the basic configuration options that any SVM modeler needs.

Constructor & Destructor Documentation

function SVMFactory ( var  varargin)
inline

Class constructor.

Returns
instance of the class

Member Function Documentation

function createInitialModels ( var  number,
var  wantModels 
)

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)

TODO.

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

function createRandomModel ( )

TODO.

Return a randomly chosen SVM model.

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

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 ( )
inline

TODO.

function getBasicBatchObservables ( )
inherited

TODO.

Generate the observable objects that handle grouped data.

function getBatchObservables ( )
inlineinherited

TODO.

function getBounds ( )
inline

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 ( )
inline

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 ( )
inline

TODO.

function isCustomMode ( )
inlineinherited

TODO.

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

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 ( )
inline

TODO.

function supportsMultipleOutputs ( )
inline

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

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