代码搜索：optimisation
找到约 403 项符合「optimisation」的源代码
代码结果 403
www.eeworm.com/read/255755/12057397
m parzenc.m
%PARZENC Optimisation of the Parzen classifier
%
% [W,H] = PARZENC(A)
% W = PARZENC(A,H,FID)
%
% INPUT
% A dataset
% H smoothing parameter (may be scalar, vector of per-class
% param
www.eeworm.com/read/150905/12248512
m parzenc.m
%PARZENC Optimisation of the Parzen classifier
%
% [W,H] = PARZENC(A)
% W = PARZENC(A,H,FID)
%
% INPUT
% A dataset
% H smoothing parameter (may be scalar, vector of per-class
% param
www.eeworm.com/read/150884/12252925
py fitfun.py
"""Fitness functions for use in genetic algorithm
optimisation
$Id: FitFun.py Copyright (C) 2005 Roger Jarvis
This program is free software; you can redistribute it and/or
modify it under the
www.eeworm.com/read/149739/12352830
m parzenc.m
%PARZENC Optimisation of the Parzen classifier
%
% [W,H] = PARZENC(A)
% W = PARZENC(A,H,FID)
%
% INPUT
% A dataset
% H smoothing parameter (may be scalar, vector of per-class
% param
www.eeworm.com/read/456564/1605063
cc splinematrix.cc
//
// SplineMatrix.h
//
// class with methods to convert a RegionBoundary to spline form.
//
// (added reparametrisation optimisation method 14/12/94)
//
//
#include
#include
#in
www.eeworm.com/read/456564/1605086
h splinematrix.h
//
// SplineMatrix.h
//
// class with methods to convert a RegionBoundary to spline form.
//
// (added reparametrisation optimisation method 14/12/94)
//
//
#ifndef __SPLINE_MATRIX__
#define __SPLIN
www.eeworm.com/read/375719/9351853
m get.m
function out = get(quiz,info,index)
% SDMPB/GET - get information on a SDMPB object
%
% out = get(quiz,info,index);
%
% is a SDMPB object that describes a linear optimisation problem
%
www.eeworm.com/read/491223/6437606
readme
This package contains the Matlab source code of paper Q. Zhang, A. Zhou, Y. Jin. 'Modelling the Regularity in an Estimation of Distribution Algorithm for Continuous Multiobjective Optimisation with Va
www.eeworm.com/read/407072/2270942
hpp flags.hpp
#ifndef INDII_ML_FILTER_FLAGS_HPP
#define INDII_ML_FILTER_FLAGS_HPP
/**
* @file flags.hpp
*
* Optimisation flags for KernelForwardBackwardSmoother and
* KernelTwoFilterSmoother.
*/
namespace in
www.eeworm.com/read/289680/8535103
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut