代码搜索：usage
找到约 10,000 项符合「usage」的源代码
代码结果 10,000
www.eeworm.com/read/492929/6414229
m lad.m
function results = lad(y,x,maxit,crit)
% PURPOSE: least absolute deviations regression
% --------------------------------------------------
% USAGE: results = lad(y,x,itmax,convg)
% where: y
www.eeworm.com/read/492929/6414243
m olsrs.m
function results = olsrs(y,x,R,q)
% PURPOSE: Restricted least-squares estimation
% y = Xb + e with the constraint that q = Rb
%---------------------------------------------------
% USAGE: results
www.eeworm.com/read/487311/6519043
l ch2-06.l
%{
#undef input
#undef unput
unsigned verbose;
unsigned fname;
char *progName;
%}
%s FNAME
%%
[ ]+ /* ignore blanks */ ;
[ ]+ /* ignore blanks */ ;
-h |
"-?" |
-help { printf("usage
www.eeworm.com/read/484356/6586032
m featselregspanboundgd.m
function [RankedVariables,nbsvvec,Values,NbQP,NbInv,iter]=FeatSelspanboundGD(x,y,c,epsilon,kernel,kerneloption,verbose,FeatSeloption)
% USAGE
%
% [RankedVariables,nbsvvec,Values]=FeatSelspanbo
www.eeworm.com/read/484356/6586033
m featselregalphagd.m
function [RankedVariables,nbsvvec,Values,NbQP,iter]=FeatSelregalphaGD(x,y,c,epsilon,kernel,kerneloption,verbose,FeatSeloption)
% Usage
%
% [RankedVariables,nbsvvec,Values,NbQP]=FeatSelregalpha
www.eeworm.com/read/484356/6586038
m featselregmargingdrandom.m
function [RankedVariables,nbsvvec,Values,NbQP,iter]=FeatSelregmarginGDrandom(x,y,c,epsilon,kernel,kerneloption,verbose,FeatSeloption)
% Usage
%
% [RankedVariables,nbsvvec,Values,NbQP]=FeatSelr
www.eeworm.com/read/484356/6586044
m featselregmargingd.m
function [RankedVariables,nbsvvec,Values,NbQP,iter]=FeatSelregmarginGD(x,y,c,epsilon,kernel,kerneloption,verbose,FeatSeloption)
% Usage
%
% [RankedVariables,nbsvvec,Values,NbQP]=FeatSelregmarg
www.eeworm.com/read/484356/6586058
m createmultilevelkernel.m
function [K,Kt]=CreateMultiLevelKernel(xapp,xtest,kerneloption,level)
% USAGE
%
% [K,Kt]=CreateMultiLevelKernel(xapp,xtest,kerneloption,level)
%
% This function creates multiscale kernels K an
www.eeworm.com/read/484356/6586079
m kernelpca.m
function [eigvect,eigval,Kt]=kernelpca(x,kernel,kerneloption)
% USAGE
% [eigvect,eigval]=kernelpca(x,kernel,kerneloption)
%
% Diagonalizing the covariance matrix in feature space
%
% eigenv
www.eeworm.com/read/484356/6586098
m rankboostaucold.m
function [alpha,threshold,rankfeat]=rankboostAUC(xapp,yapp,T);
% USAGE
%
% [alpha,threshold,rankfeat]=rankboostAUC(xapp,yapp,T);
%
% This a Rankboost algorithm as described in the freund et