代码搜索：classifiers
找到约 2,305 项符合「classifiers」的源代码
代码结果 2,305
www.eeworm.com/read/135153/5889763
h cls_rsvp.h
/*
* net/sched/cls_rsvp.h Template file for RSVPv[46] classifiers.
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
www.eeworm.com/read/493294/6399974
m rankboostc.m
function W = rankboostc(a,fracrej,T)
%RANKBOOSTB Binary rankboost
%
% W = RANKBOOSTC(A,FRACREJ,T)
%
% Train a simple binary version of rankboost containing T weak
% classifiers. The base (weak) cla
www.eeworm.com/read/493294/6400015
m normal_map.m
%NORMAL_MAP Map a dataset on normal-density classifiers or mappings
%
% F = NORMAL_MAP(A,W)
%
% INPUT
% A Dataset
% W Mapping
%
% OUTPUT
% F Density estimation for classes in A
%
% DESC
www.eeworm.com/read/492400/6422241
m rankboostc.m
function W = rankboostc(a,fracrej,T)
%RANKBOOSTB Binary rankboost
%
% W = RANKBOOSTC(A,FRACREJ,T)
%
% Train a simple binary version of rankboost containing T weak
% classifiers. The base (weak) cla
www.eeworm.com/read/400577/11572704
m normal_map.m
%NORMAL_MAP Map a dataset on normal-density classifiers or mappings
%
% F = NORMAL_MAP(A,W)
%
% INPUT
% A Dataset
% W Mapping
%
% OUTPUT
% F Density estimation for classes in A
%
% DESC
www.eeworm.com/read/342008/12047428
m mclassc.m
%MCLASSC Computation of multi-class classifier from 2-class discriminants
%
% W = mclassc(A,classf)
%
% The untrained classifier classf is called to compute c classifiers
% between each of the c class
www.eeworm.com/read/255755/12057417
m normal_map.m
%NORMAL_MAP Map a dataset on normal-density classifiers or mappings
%
% F = NORMAL_MAP(A,W)
%
% INPUT
% A Dataset
% W Mapping
%
% OUTPUT
% F Density estimation for classes in A
%
% DESC
www.eeworm.com/read/150905/12248535
m normal_map.m
%NORMAL_MAP Map a dataset on normal-density classifiers or mappings
%
% F = NORMAL_MAP(A,W)
%
% INPUT
% A Dataset
% W Mapping
%
% OUTPUT
% F Density estimation for classes in A
%
% DESC
www.eeworm.com/read/149739/12352845
m normal_map.m
%NORMAL_MAP Map a dataset on normal-density classifiers or mappings
%
% F = NORMAL_MAP(A,W)
%
% INPUT
% A Dataset
% W Mapping
%
% OUTPUT
% F Density estimation for classes in A
%
% DESC
www.eeworm.com/read/213240/15139984
m rankboostc.m
function W = rankboostc(a,fracrej,T)
%RANKBOOSTB Binary rankboost
%
% W = RANKBOOSTC(A,FRACREJ,T)
%
% Train a simple binary version of rankboost containing T weak
% classifiers. The base (weak) cla