代码搜索：separable
找到约 238 项符合「separable」的源代码
代码结果 238
www.eeworm.com/read/366959/2857621
m linsvm.m
function [alpha,theta,solution]=linsvm(X,J)
% LINSVM Support Vector Machines for the linear and separable case.
% [alpha,theta,solution]=linsvm(X,J)
%
% LINSVM is an implementation of the Support Vec
www.eeworm.com/read/266483/4272256
m linsvm.m
function [alpha,theta,solution]=linsvm(X,J)
% LINSVM Support Vector Machines for the linear and separable case.
% [alpha,theta,solution]=linsvm(X,J)
%
% LINSVM is an implementation of the Support Vec
www.eeworm.com/read/292863/8328503
m wpyrband.m
% RES = wpyrBand(PYR, INDICES, LEVEL, BAND)
%
% Access a subband from a separable QMF/wavelet pyramid.
%
% LEVEL (optional, default=1) indicates the scale (finest = 1,
% coarsest = wpyrHt(INDI
www.eeworm.com/read/292863/8328582
m wpyrband.m
% RES = wpyrBand(PYR, INDICES, LEVEL, BAND)
%
% Access a subband from a separable QMF/wavelet pyramid.
%
% LEVEL (optional, default=1) indicates the scale (finest = 1,
% coarsest = wpyrHt(INDI
www.eeworm.com/read/367442/9748175
m linsvm.m
function [alpha,theta,solution]=linsvm(X,J)
% LINSVM Support Vector Machines for the linear and separable case.
% [alpha,theta,solution]=linsvm(X,J)
%
% LINSVM is an implementation of the Support Vec
www.eeworm.com/read/428849/8834548
m genlsdata.m
function [data,model] = genlsdata( dim, num_data, margin )
% GENLSDATA Generates linearly separable binary data.
%
% Synopsis:
% data = genlsdata(dim,num_data,margin)
%
% Description:
% It generates
www.eeworm.com/read/184617/9091702
m svmlspex02.m
%SVMLSPex02.m
%Two Dimension SVM Problem, Two Class and Separable Situation
%
%%Difference with SVMLSPex01.m:
% Take the Largrange Function (16)as object function insteads ||W||,
% s
www.eeworm.com/read/184617/9091729
m svmnlusex01.m
%SVMnLSPex01.m
%(Another expression of Object and constraint Function With Matrix Style)
%Two Dimension SVM Problem, Two Class and Un-separable Situation
%
%Method from Thorsten Joachims:
%"Makin
www.eeworm.com/read/362246/10009996
m genlsdata.m
function [data,model] = genlsdata( dim, num_data, margin )
% GENLSDATA Generates linearly separable binary data.
%
% Synopsis:
% data = genlsdata(dim,num_data,margin)
%
% Description:
% It generates
www.eeworm.com/read/280595/10311642
m genlsdata.m
function [data,model] = genlsdata( dim, num_data, margin )
% GENLSDATA Generates linearly separable binary data.
%
% Synopsis:
% data = genlsdata(dim,num_data,margin)
%
% Description:
% It generates