代码搜索：classifier

找到约 4,824 项符合「classifier」的源代码

代码结果 4,824
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www.eeworm.com/read/299984/7140680

m mclassc.m

%MCLASSC Computation of multi-class classifier from 2-class discriminants % % W = MCLASSC(A,CLASSF,MODE) % % INPUT % A Dataset % CLASSF Untrained classifier % MODE Type of handling mu
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www.eeworm.com/read/299984/7140766

m rsscc.m

%RSSCC Random subspace combining classifier % % W = RSSCC(A,CLASSF,NFEAT,NCLASSF) % % INPUT % A Dataset % CLASSF Untrained base classifier % NFEAT Number of features for train
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www.eeworm.com/read/462231/7206015

makefile

# Copyright (c) 1994, 1995, 1996 # The Regents of the University of California. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are
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www.eeworm.com/read/460435/7250467

m knnc.m

%KNNC K-Nearest Neighbor Classifier % % [W,K,E] = KNNC(A,K) % [W,K,E] = KNNC(A) % % INPUT % A Dataset % K Number of the nearest neighbors (optional; default: K is % optimized with resp
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www.eeworm.com/read/460435/7250503

m pcldc.m

%PCLDC Linear classifier using PC expansion on the joint data. % % W = PCLDC(A,N) % W = PCLDC(A,ALF) % % INPUT % A Dataset % N Number of eigenvectors % ALF Total explained variance (defau
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www.eeworm.com/read/460435/7250783

m kernelc.m

%KERNELC Arbitrary kernel/dissimilarity based classifier % % W = KERNELC(A,KERNEL,CLASSF) % W = A*KERNELC([],KERNEL,CLASSF) % % INPUT % A Dateset used for training % KERNEL - unt
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www.eeworm.com/read/460435/7251035

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%FDSC Feature based Dissimilarity Space Classification (outdated) % % This routine is outdated, use KERNELC instead % % W = FDSC(A,R,FEATMAP,TYPE,P,CLASSF) % W = A*FDSC([],R,FEATMAP,TYPE,P,C
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www.eeworm.com/read/460435/7251156

m mclassc.m

%MCLASSC Computation of multi-class classifier from 2-class discriminants % % W = MCLASSC(A,CLASSF,MODE) % % INPUT % A Dataset % CLASSF Untrained classifier % MODE Type of handling mu
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www.eeworm.com/read/460435/7251248

m rsscc.m

%RSSCC Random subspace combining classifier % % W = RSSCC(A,CLASSF,NFEAT,NCLASSF) % % INPUT % A Dataset % CLASSF Untrained base classifier % NFEAT Number of features for train
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www.eeworm.com/read/458392/7297128

m svmmulticlassoneagainstone.m

function [xsup,w,b,nbsv,classifier,pos,obj]=svmmulticlassoneagainstone(x,y,nbclass,c,epsilon,kernel,kerneloption,verbose,warmstart); %[xsup,w,b,nbsv,classifier,posSigma]=svmmulticlassoneagainstone(x,
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