代码搜索：classifiers
找到约 2,305 项符合「classifiers」的源代码
代码结果 2,305
www.eeworm.com/read/143005/5761496
dta class100.dta
6 // nposition *** class100.dta ***
100 // nclassifier
0.5 // pgeneral
0.10 // cbid
0.075 // bidsigma
0.01 // bidtax
0.0 // lifetax
0.25 // bid 1
0.125 // bid 2
0.25 // ebid 1
0.125 // ebi
www.eeworm.com/read/143005/5761502
dta class100.dta
6 // nposition *** class100.dta ***
100 // nclassifier
0.5 // pgeneral
0.10 // cbid
0.075 // bidsigma
0.01 // bidtax
0.0 // lifetax
0.25 // bid 1
0.125 // bid 2
0.25 // ebid 1
0.125 // ebi
www.eeworm.com/read/493294/6399875
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/493294/6400340
m prex_combining.m
%PREX_COMBINING PRTools example on classifier combining
%
% Presents the use of various fixed combiners for some
% classifiers on the 'difficult data'.
%
help prex_combining
echo on
www.eeworm.com/read/400577/11572574
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/400577/11573213
m prex_combining.m
%PREX_COMBINING PRTools example on classifier combining
%
% Presents the use of various fixed combiners for some
% classifiers on the 'difficult data'.
%
help prex_combining
echo on
www.eeworm.com/read/342008/12047464
m prex2.m
%PREX2 PRTOOLS example, plot learning curves of classifiers
help prex2
pause(1)
echo on
% set desired learning sizes
learnsize = [3 5 10 15 20 30];
% Generate Highleyman's classes
A = gend
www.eeworm.com/read/255755/12057204
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/255755/12058027
m prex_combining.m
%PREX_COMBINING PRTools example on classifier combining
%
% Presents the use of various fixed combiners for some
% classifiers on the 'difficult data'.
%
help prex_combining
echo on
www.eeworm.com/read/150905/12248259
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT