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/493294/6399951
m polyc.m
%POLYC Polynomial Classification
%
% W = polyc(A,CLASSF,N,S)
%
% INPUT
% A Dataset
% CLASSF Untrained classifier (optional; default: FISHERC)
% N Degree of polynomial (optional;
www.eeworm.com/read/493294/6400277
m featseli.m
%FEATSELI Individual feature selection for classification
%
% [W,R] = FEATSELI(A,CRIT,K,T)
%
% INPUT
% A Training dataset
% CRIT Name of the criterion or untrained mapping
% (default:
www.eeworm.com/read/493294/6400478
m featrank.m
%FEATRANK Feature ranking on individual performance for classification
%
% [I,F] = FEATRANK(A,CRIT,T)
%
% INPUT
% A input dataset
% CRIT string name of a method or untrained mapp
www.eeworm.com/read/483114/6609673
m getkernel.m
function kernel = getkernel(net)
% GETKERNEL
%
% Accessor method returning the kernel used in a support vector classification
% network.
%
% ker = getkernel(net)
%
% File : @svc/
www.eeworm.com/read/400577/11572646
m polyc.m
%POLYC Polynomial Classification
%
% W = polyc(A,CLASSF,N,S)
%
% INPUT
% A Dataset
% CLASSF Untrained classifier (optional; default: FISHERC)
% N Degree of polynomial (optional;
www.eeworm.com/read/400577/11573005
m featseli.m
%FEATSELI Individual feature selection for classification
%
% [W,R] = FEATSELI(A,CRIT,K,T)
%
% INPUT
% A Training dataset
% CRIT Name of the criterion or untrained mapping
% (default:
www.eeworm.com/read/400577/11573359
m featrank.m
%FEATRANK Feature ranking on individual performance for classification
%
% [I,F] = FEATRANK(A,CRIT,T)
%
% INPUT
% A input dataset
% CRIT string name of a method or untrained mapp
www.eeworm.com/read/157337/11718869
m facerecexplanation.m
%FISHERFACES FOR FACE RECOGNITION
%
% We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression.
% Taking a pattern classification
www.eeworm.com/read/255755/12057320
m polyc.m
%POLYC Polynomial Classification
%
% W = polyc(A,CLASSF,N,S)
%
% INPUT
% A Dataset
% CLASSF Untrained classifier (optional; default: FISHERC)
% N Degree of polynomial (optional;
www.eeworm.com/read/255755/12057929
m featseli.m
%FEATSELI Individual feature selection for classification
%
% [W,R] = FEATSELI(A,CRIT,K,T)
%
% INPUT
% A Training dataset
% CRIT Name of the criterion or untrained mapping
% (default: