代码搜索：classification
找到约 3,679 项符合「classification」的源代码
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www.eeworm.com/read/357874/10199056
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/280638/10301621
m pnn1.m
%% PNN Classification
% This demonstration uses functions NEWPNN and SIM.
%
% Copyright 1992-2002 The MathWorks, Inc.
% $Revision: 1.9 $ $Date: 2002/03/29 19:36:07 $
%%
% Here are three two-el
www.eeworm.com/read/161855/10360967
1 dbacl.1
\" t
.TH DBACL 1 "Bayesian Text Classification Tools" "Version 1.3" ""
.SH NAME
dbacl \- a digramic Bayesian classifier for text recognition.
.SH SYNOPSIS
.HP
.B dbacl
[-dvnirMND]
[-T
.IR type
] -l
www.eeworm.com/read/160933/10469238
m svcm_test.m
function [ypred,indw] = svcm_test(xtest,ytest,xtrain,ytrain,atrain,btrain);
% function [ypred,indw] = svcm_test(xtest,ytest,xtrain,ytrain,atrain,btrain);
%
% support vector classification machine
% te
www.eeworm.com/read/351797/10609685
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/469123/6977870
m demo_ep_2d.m
% demonstrate the Expectation Propagation approximation on a 2-d
% classification task. 2006-03-29.
if isempty(regexp(path,['gpml' pathsep]))
cd ..; w = pwd; addpath([w, '/gpml']); cd gpml-demo
www.eeworm.com/read/469123/6977874
m demo_ep_usps.m
% Demo script to illustrate use of binaryEP on a binary digit classification
% task. 2006-03-29.
if isempty(regexp(path,['gpml' pathsep]))
cd ..; w = pwd; addpath([w, '/gpml']); cd gpml-demo % a
www.eeworm.com/read/461039/7235538
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/458392/7297164
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