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CG(derived) OPTIMIZATION ALGORITHMS CG(derived) Jun 1 15:17NAME CG - Conjugate GradientSYNOPSIS #include <CG.hh> class ConjugateGradient : public LineSearchOptima \fIPublic members\fP ConjugateGradient(LineSearch*, int, double); ConjugateGradient(LineSearch*, int, double, int); ~ConjugateGradient(); Model<double> optimizer(Model<double>&); Model<long> optimizer(Model<long>&); const char* className() const;DESCRIPTION ConjugateGradient() The conjugate gradient procedure implemented in this object is an extension of the conjugate gradient used in linear system solving to handle non quadratic objective functions. Such extensions amount basically to the inclusion of a line search step and a modification in the computation of the conjugate directions. Details can be found in the classic (and tough!) book Practical Optimization by Powell. DESCRIPTION Constructors: ConjugateGradient(LineSearch* ls, int iter, double tol) ls: Defines the line search used. At the present version you should use the CubicLineSearch procedure. iter: Maximum number of iterations tol: Minimum accepted module of the gradient at optimum solution Methods: optimizer(Model<double>&) model0: Initial model for the conjugate gradient procedure. The optimum model is returned by the function. CAVEATS This procedure requires the derivatives of the objective function. At the present version the COOOL library cannot handle analytic derivatives provided by the user. Here the derivatives are computed numerically by a centered finite differencing scheme in a automatic fashion. The hability to support user-provided derivatives will hopefully be implemented in the near future.DEFINED MACROS CONJUGATE_GRADIENT_HHINCLUDED FILES "LSearchOptima.hh"SOURCE FILES CG.cc
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