代码搜索:2000

找到约 10,000 项符合「2000」的源代码

代码结果 10,000
www.eeworm.com/read/242302/13053400

html 15191.html

Re: 第一个解答小弟以下问题者,奉上束脩2000元 Re: 第一个解答小弟以下问题者,奉上束脩2000
www.eeworm.com/read/242302/13057693

html 20847.html

请问!有人知道如何在VB6连接OFFIICE2000吗? 请问!有人知道如何在VB6连接OFFIICE2000吗?
www.eeworm.com/read/140850/13059486

m svc.m

function net = svc(arg, sv, w, bias) % SVC % % Construct a support vector classification (SVC) network object. % % Examples: % % % default constructor (linear, hardmargin SVC with no suppo
www.eeworm.com/read/140850/13059536

m evaluate.m

function K = evaluate(ker, x1, x2) % EVALUATE % % Evaluate a Gaussian radial basis kernel, for example % % K = evaluate(kernel, x1, x2); % % where x1 and x2 are matrices containing input p
www.eeworm.com/read/140850/13059591

h infcache.h

/****************************************************************************** File : InfCache.h Date : Wednesday 13th September 2000 Author : Dr Gavin C. Cawley Descri
www.eeworm.com/read/140850/13059594

hh utils.hh

/****************************************************************************** File : utils.hh Date : Wednesday 13th September 2000 Author : Dr Gavin C. Cawley Descript
www.eeworm.com/read/140850/13059597

m smosvctutor.m

function tutor = smosvctutor(arg) % SMOSVCTUTOR % % Construct a tutor object for training support vector classifiers using the % sequential minimal optimisation algorithm. % % Examples: % %
www.eeworm.com/read/140850/13059603

h cache.h

/****************************************************************************** File : Cache.h Date : Wednesday 13th September 2000 Author : Dr Gavin C. Cawley Descripti
www.eeworm.com/read/140850/13059633

m polynomial.m

function ker = polynomial(arg) % POLYNOMIAL % % Construct a polynomial kernel object, % % K(x1, x2) = (x1*x2' + 1).^d; % % Examples: % % % default constructor (quadratic kernel, d = 2
www.eeworm.com/read/140850/13059636

m evaluate.m

function K = evaluate(ker, x1, x2) % EVALUATE % % Evaluate a polynomial kernel, for example % % K = evaluate(kernel, x1, x2); % % where x1 and x2 are matrices containing input patterns, wh