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/204456/15339369
m dd_error.m
function [e,f] = dd_error(x,w)
%DD_ERROR compute false positive and false negative for oc_classifier
%
% E = DD_ERROR(X,W)
% E = DD_ERROR(X*W)
% E = X*W*DD_ERROR
%
% Compute the fraction of targ
www.eeworm.com/read/159921/10587754
m knnclass.m
% KNNCLASS k-Nearest Neighbours classifier.
% [tst_labels] = knnclass(tst_data,trn_data,trn_labels, k)
%
% Input:
% tst_data [dim x n_tst] data to be classified.
% trn_data [dim x n_trn] training da
www.eeworm.com/read/421949/10676406
m knnclass.m
% KNNCLASS k-Nearest Neighbours classifier.
% [tst_labels] = knnclass(tst_data,trn_data,trn_labels, k)
%
% Input:
% tst_data [dim x n_tst] data to be classified.
% trn_data [dim x n_trn] training da
www.eeworm.com/read/143706/12850035
m mcbagging.m
function [Y_compute, Y_prob] = MCBagging(classifier, para, X_train, Y_train, X_test, Y_test, num_class)
rand('state', 40);
class_set = GetClassSet(Y_train);
p = str2num(char(ParseParameter(para
www.eeworm.com/read/322475/13379429
m knn.m
function [class]=knn(Pr,Tr,Pt,kN)
% Usage: [Cmat,C_rate]=knn(Pr,Tr,Pt,Tt,kN)
% kNN- k-Nearest Neighbor Classifier
% copyright 1993-1996 by Yu Hen Hu
% Last revision 2/12/03 by Marco F. Duarte
% Pr: t
www.eeworm.com/read/128293/5992022
entries
/ArticleBatch.java/1.4/Tue Jun 22 09:58:58 2004//
/ArticleClassify.java/1.3/Fri Apr 30 08:24:30 2004//
/ArticleDomParser.java/1.4/Sun Jun 13 09:45:41 2004//
/Classifier.java/1.3/Fri Apr 30 08:24:31
www.eeworm.com/read/229007/14355754
m knn.m
function [class]=knn(Pr,Tr,Pt,kN)
% Usage: [Cmat,C_rate]=knn(Pr,Tr,Pt,Tt,kN)
% kNN- k-Nearest Neighbor Classifier
% copyright 1993-1996 by Yu Hen Hu
% Last revision 2/12/03 by Marco F. Duarte
% Pr: t
www.eeworm.com/read/124397/14569786
m hmmrecog.m
function [logp,guess] = hmmrecog(data,A_m,B_m,pi_m,cb,N,deltaN,M,Q)
% hmmrecog --> HMM based word classifier.
%
%
% [logp,guess] = hmmrecog(data,A_m,B_m,pi_m,cb,N,deltaN,M,Q)
%
%
www.eeworm.com/read/223154/14651923
m fc0.m
function [CC,Q,tsd,md,cc]=fc0(D,TRIG,T,arg4)
% FC finds a classifier for asnychroneous data
%
% [CC,Q,TSD,MD]=fc0(D,TRIG,class_times [,SWITCH]);
%
% D data, each row is one time point
% TRIG t
www.eeworm.com/read/250585/4428754
entries
/BVDecompose.java/1.1/Tue May 1 13:10:07 2007//
/BVDecomposeSegCVSub.java/1.1/Tue May 1 13:10:08 2007//
/CheckClassifier.java/1.1/Tue May 1 13:10:08 2007//
/Classifier.java/1.1/Tue May 1 13:10: