代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/201218/15413209
m trainlssvm.m
function [model,b,X,Y] = trainlssvm(model,X,Y)
% Train the support values and the bias term of an LS-SVM for classification or function approximation
%
% >> [alpha, b] = trainlssvm({X,Y,type,gam,ke
www.eeworm.com/read/111603/15509328
m fwd.m
function y = fwd(net,x)
% FWD
%
% Compute the output of a multi-class support vector classification network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, where each colu
www.eeworm.com/read/111603/15509378
m fwd.m
function y = fwd(net,x)
% FWD
%
% Compute the output of a multi-class support vector classification network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, where each colu
www.eeworm.com/read/111603/15509381
m fwd.m
function y = fwd(net, x)
% FWD
%
% Compute the output of a dag-svm multi-class support vector classification
% network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, in
www.eeworm.com/read/289680/8535004
m maxwin.m
function net = maxwin(arg, sv, w, bias, C, zeta)
% MAXWIN
%
% Construct a max-win multi-class support vector classification network.
%
% Examples:
%
% % default constructor (a 0-class maxw
www.eeworm.com/read/289488/8548337
m exnuclass1.m
%
% SVM Classification 2D examples
% with different kernels (including wavelets) and different penalization settings
%
% 05/05/03 AR
clear all
close all
n = 100;
sigma=0.4;
[Xapp,yapp,xtest,yt
www.eeworm.com/read/289487/8548586
m exmultikernellarclass.m
%
% Example of KBP applied on a classification problem
%
% 20/12/05 AR
clear all
close all
n = 500;
sigma=0.4;
[xapp,yapp,xtest,ytest]=dataset('checkers',n,0,sigma);
[xapp]=normalizemeanstd(xap
www.eeworm.com/read/188280/8552150
m maxwin.m
function net = maxwin(arg, sv, w, bias, C, zeta)
% MAXWIN
%
% Construct a max-win multi-class support vector classification network.
%
% Examples:
%
% % default constructor (a 0-class maxw
www.eeworm.com/read/286662/8751662
m genetic_programming.m
function [test_targets, best_fun] = genetic_programming(train_patterns, train_targets, test_patterns, params)
% A genetic programming algorithm for classification
%
% train_patterns - Train patt
www.eeworm.com/read/384512/8866157
m som_clustercolor.m
function color=som_clustercolor(m, class, colorcode)
% SOM_CLUSTERCOLOR Sets map unit coloring according to classification
%
% syntax 1: color = som_clustercolor(m, class, [colorcode])
% syntax 2: c