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/255755/12057216
m feateval.m
%FEATEVAL Evaluation of feature set for classification
%
% J = FEATEVAL(A,CRIT,T)
% J = FEATEVAL(A,CRIT,N)
%
% INPUT
% A input dataset
% CRIT string name of a method or untraine
www.eeworm.com/read/255755/12058309
m featselb.m
%FEATSELB Backward feature selection for classification
%
% [W,R] = FEATSELB(A,CRIT,K,T,FID)
%
% INPUT
% A Dataset
% CRIT String name of the criterion or untrained mapping
% (opti
www.eeworm.com/read/152929/12073895
m multclas.m
% General purpose Growing Cell Structure Visualisation and Classification
% multclas(train,test,NoClasses,NoNewNodes,epochspernode,smooth,metric,netname)
%
function multclas(train,test,NoClasses,No
www.eeworm.com/read/254141/12158969
txt itu_terminals_for_telematic_services.txt
ITU Terminals for telematic services
T.0
Classification of facsimile terminals for document transmission over the public networks
T.1
Standardization of phototelegraph apparatus
www.eeworm.com/read/150905/12248270
m feateval.m
%FEATEVAL Evaluation of feature set for classification
%
% J = FEATEVAL(A,CRIT,T)
% J = FEATEVAL(A,CRIT,N)
%
% INPUT
% A input dataset
% CRIT string name of a method or untraine
www.eeworm.com/read/150905/12249691
m featselb.m
%FEATSELB Backward feature selection for classification
%
% [W,R] = FEATSELB(A,CRIT,K,T,FID)
%
% INPUT
% A Dataset
% CRIT String name of the criterion or untrained mapping
% (opti
www.eeworm.com/read/150760/12264733
m contents.m
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.05 19-Oct-2005
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/150760/12266225
m~ contents.m~
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.04 22-Dec-2004
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/149739/12352654
m feateval.m
%FEATEVAL Evaluation of feature set for classification
%
% J = FEATEVAL(A,CRIT,T)
% J = FEATEVAL(A,CRIT,N)
%
% INPUT
% A input dataset
% CRIT string name of a method or untraine
www.eeworm.com/read/149739/12353947
m featselb.m
%FEATSELB Backward feature selection for classification
%
% [W,R] = FEATSELB(A,CRIT,K,T,FID)
%
% INPUT
% A Dataset
% CRIT String name of the criterion or untrained mapping
% (opti