代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/328078/13047198
m disp.m
function c = disp(f)
%CLASSIFIER/DISP Display CLASSIFIER object.
% Copyright (c) 1999 Michael Kiefte.
% $Log$
n = f.counts;
g = length(n);
prior = f.prior;
if isempty(prior)
prior = n./sum(n)
www.eeworm.com/read/328078/13047213
m cvar.m
function [lambda, ratio] = cvar(f)
%LDA/CVAR Fisher's linear discriminant analysis.
% [LAMBDA, RATIO] = CVAR(F) return the canonical variates of the
% Fisher's linear discriminant analysis in the
www.eeworm.com/read/328078/13047214
m subsref.m
function g = subsref(f, s)
%LDA/SUBSREF Subscripted reference of LDA object.
% Copyright (c) 1999 Michael Kiefte
% $Log$
switch s(1).type
case '.'
switch s(1).subs
case 'means'
h
www.eeworm.com/read/327199/13095493
plg svmcls.plg
Build Log
--------------------Configuration: svmcls - Win32 Debug--------------------
Command Lines
Creating command line "rc.exe /l 0x804 /fo"
www.eeworm.com/read/139615/13147062
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/240981/13183333
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 per
www.eeworm.com/read/138830/13208887
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/137160/13341920
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/137160/13342352
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/137160/13342373
m fdsc.m
%FDSC Feature based Dissimilarity Space Classification
%
% W = FDSC(A,R,FEATMAP,TYPE,P,CLASSF)
% W = A*FDSC([],R,FEATMAP,TYPE,P,CLASSF)
%
% INPUT
% A Dateset used for training
% R