代码搜索:classification

找到约 3,679 项符合「classification」的源代码

代码结果 3,679
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m fwd.m

function y = fwd(net,x) % FWD % % Compute the output of a support vector classification network. % % y = fwd(net, x); % % where x is a matrix of input patterns, where each column represent
www.eeworm.com/read/188280/8552146

m fwd.m

function y = fwd(net,x) % FWD % % Compute the output of a support vector classification network. % % y = fwd(net, x); % % where x is a matrix of input patterns, where each column represent
www.eeworm.com/read/386050/8767352

m gendats.m

%GENDATS Generation of a simple classification problem of 2 Gaussian classes % % A = GENDATS (N,K,D,LABTYPE) % % INPUT % N Dataset size, or 2-element array of class sizes (default: [50 50]
www.eeworm.com/read/386050/8768247

m gentrunk.m

%GENTRUNK Generation of Trunk's classification problem of 2 Gaussian classes % % A = GENTRUNK(N,K) % % INPUT % N Dataset size, or 2-element array of class sizes (default: [50 50]). % K
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m featself.m

%FEATSELF Forward feature selection for classification % % [W,R] = FEATSELF(A,CRIT,K,T,FID) % [W,R] = FEATSELF(A,CRIT,K,N,FID) % % INPUT % A Training dataset % CRIT Name of the criterion or u
www.eeworm.com/read/386050/8769028

m fdsc.m

%FDSC Feature based Dissimilarity Space Classification (outdated) % % This routine is outdated, use KERNELC instead % % W = FDSC(A,R,FEATMAP,TYPE,P,CLASSF) % W = A*FDSC([],R,FEATMAP,TYPE,P,C
www.eeworm.com/read/386050/8769501

m featselb.m

%FEATSELB Backward feature selection for classification % % [W,R] = FEATSELB(A,CRIT,K,T,FID) % [W,R] = FEATSELB(A,CRIT,K,N,FID) % % INPUT % A Dataset % CRIT String name of the criterion o
www.eeworm.com/read/386050/8769511

m featsellr.m

%FEATSELLR Plus-L-takeaway-R feature selection for classification % % [W,RES] = FEATSELLR(A,CRIT,K,L,R,T,FID) % % INPUT % A Dataset % CRIT String name of the criterion or untrained mapping
www.eeworm.com/read/428451/8867247

m code.m

function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args) % Encode and decode a multi-class classification task into multiple binary cl
www.eeworm.com/read/427586/8932057

m code.m

function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args) % Encode and decode a multi-class classification task into multiple binary cl