代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/476117/6763119
cpp scs.cpp
/****************************************************************************/
/* 基本遗传学习分类系统 SCS.CPP */
/* A Simple Classifier System based on G
www.eeworm.com/read/264792/11301197
makefile
# Generated automatically from Makefile.in by configure.
# Copyright (c) 1994, 1995, 1996
# The Regents of the University of California. All rights reserved.
#
# Redistribution and use in source a
www.eeworm.com/read/264052/11331331
cpp scs.cpp
/****************************************************************************/
/* 基本遗传学习分类系统 SCS.CPP */
/* A Simple Classifier System based on G
www.eeworm.com/read/408453/11387867
plg svmcls.plg
Build Log
--------------------Configuration: svmcls - Win32 Debug--------------------
Command Lines
Creating command line "rc.exe /l 0x804 /fo"
www.eeworm.com/read/407588/11414477
cpp scs.cpp
/****************************************************************************/
/* 基本遗传学习分类系统 SCS.CPP */
/* A Simple Classifier System based on G
www.eeworm.com/read/401027/11565760
cpp scs.cpp
/****************************************************************************/
/* 基本遗传学习分类系统 SCS.CPP */
/* A Simple Classifier System based on G
www.eeworm.com/read/400577/11572636
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
www.eeworm.com/read/400577/11572675
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
www.eeworm.com/read/400577/11572961
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
www.eeworm.com/read/400577/11573217
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%FDSC Feature based Dissimilarity Space Classification (outdated)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% This routine is outdated, use KERNELC instead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