@PublicationReference(author="R. Fletcher",title="Practical Methods of Optimization, Second Edition",type=Book,year=1987,pages=54,notes="Section 3.2, Equation 3.2.11") @PublicationReference(author="Wikipedia",title="Davidon-Fletcher-Powell formula",type=WebPage,year=2008,url="http://en.wikipedia.org/wiki/Davidon-Fletcher-Powell_formula") public class FunctionMinimizerDFP extends FunctionMinimizerQuasiNewton
DEFAULT_LINE_MINIMIZER, DEFAULT_MAX_ITERATIONS, DEFAULT_TOLERANCEinitialGuess, result, tolerancedata, keepGoingmaxIterationsDEFAULT_ITERATION, iteration| Constructor and Description |
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FunctionMinimizerDFP()
Creates a new instance of FunctionMinimizerBFGS
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FunctionMinimizerDFP(LineMinimizer<?> lineMinimizer)
Creates a new instance of FunctionMinimizerBFGS
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FunctionMinimizerDFP(LineMinimizer<?> lineMinimizer,
Vector initialGuess,
double tolerance,
int maxIterations)
Creates a new instance of FunctionMinimizerBFGS
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| Modifier and Type | Method and Description |
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protected boolean |
updateHessianInverse(Matrix hessianInverse,
Vector delta,
Vector gamma)
The step that makes BFGS/DFP/SR1 different from each other.
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cleanupAlgorithm, getLineMinimizer, initializeAlgorithm, setLineMinimizer, stepgetInitialGuess, getResult, getTolerance, setInitialGuess, setResult, setToleranceclone, getData, getKeepGoing, learn, setData, setKeepGoing, stopgetMaxIterations, isResultValid, setMaxIterationsaddIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, getIteration, getListeners, removeIterativeAlgorithmListener, setIteration, setListenersequals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitlearnclonegetMaxIterations, setMaxIterationsaddIterativeAlgorithmListener, getIteration, removeIterativeAlgorithmListenerisResultValid, stoppublic FunctionMinimizerDFP()
public FunctionMinimizerDFP(LineMinimizer<?> lineMinimizer)
lineMinimizer - Work-horse algorithm that minimizes the function along a directionpublic FunctionMinimizerDFP(LineMinimizer<?> lineMinimizer, Vector initialGuess, double tolerance, int maxIterations)
initialGuess - Initial guess about the minimum of the methodtolerance - Tolerance of the minimization algorithm, must be >= 0.0, typically ~1e-10lineMinimizer - Work-horse algorithm that minimizes the function along a directionmaxIterations - Maximum number of iterations, must be >0, typically ~100@PublicationReference(author="R. Fletcher", title="Practical Methods of Optimization, Second Edition", type=Book, year=1987, pages=54, notes="Section 3.2, Equation 3.2.11") protected boolean updateHessianInverse(Matrix hessianInverse, Vector delta, Vector gamma)
FunctionMinimizerQuasiNewtonupdateHessianInverse in class FunctionMinimizerQuasiNewtonhessianInverse - Current estimate of the Hessian inverse. Must be modified!delta - Change in the search points (xnew-xold)gamma - Change in the gradients (gnew-gold)