代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/450608/7480091
m minc.m
%MINC Minimum combining classifier
%
% W = MINC(V)
% W = V*MINC
%
% INPUT
% V Set of classifiers
%
% OUTPUT
% W Minimum combining classifier on V
%
% DESCRIPTION
% If V = [V1,V2,V3, ...
www.eeworm.com/read/450608/7480393
m votec.m
%VOTEC Voting combining classifier
%
% W = VOTEC(V)
% W = V*VOTEC
%
% INPUT
% V Set of classifiers
%
% OUTPUT
% W Voting combiner
%
% DESCRIPTION
% If V = [V1,V2,V3,...] is a stacked set of
www.eeworm.com/read/450608/7480583
m maxc.m
%MAXC Maximum combining classifier
%
% W = MAXC(V)
% W = V*MAXC
%
% INPUT
% V Stacked set of classifiers
%
% OUTPUT
% W Combined classifier using max-rule
%
% DESCRIPTION
% If V = [V1,V2,V
www.eeworm.com/read/450549/7481643
txt readme.txt
========================================================================
MICROSOFT FOUNDATION CLASS LIBRARY : Classifier
======================================================================
www.eeworm.com/read/441245/7672643
m minc.m
%MINC Minimum combining classifier
%
% W = MINC(V)
% W = V*MINC
%
% INPUT
% V Set of classifiers
%
% OUTPUT
% W Minimum combining classifier on V
%
% DESCRIPTION
% If V = [V1,V2,V3, ...
www.eeworm.com/read/441245/7672731
m parzenc.m
%PARZENC Optimisation of the Parzen classifier
%
% [W,H] = PARZENC(A)
% W = PARZENC(A,H,FID)
%
% INPUT
% A dataset
% H smoothing parameter (may be scalar, vector of per-class
% param
www.eeworm.com/read/441245/7672992
m adaboostc.m
%ADABOOSTC
%
% [W,V,ALF] = ADABOOSTC(A,CLASSF,N,RULE,VERBOSE);
%
% INPUT
% A Dataset
% CLASSF Untrained weak classifier
% N Number of classifiers to be trained
% RULE Combinin
www.eeworm.com/read/441245/7673027
m votec.m
%VOTEC Voting combining classifier
%
% W = VOTEC(V)
% W = V*VOTEC
%
% INPUT
% V Set of classifiers
%
% OUTPUT
% W Voting combiner
%
% DESCRIPTION
% If V = [V1,V2,V3,...] is a stacked set of
www.eeworm.com/read/441245/7673411
m maxc.m
%MAXC Maximum combining classifier
%
% W = MAXC(V)
% W = V*MAXC
%
% INPUT
% V Stacked set of classifiers
%
% OUTPUT
% W Combined classifier using max-rule
%
% DESCRIPTION
% If V = [V1,V2,V
www.eeworm.com/read/397122/8065770
m latentlssvm.m
function [zt,model] = latentlssvm(varargin)
% Calculate the latent variables of the LS-SVM classifier at the given test data
%
% >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)