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/405279/2293653
tcl flowmon.tcl
# make a flow monitor
proc makeflowmon {} {
global ns
set flowmon [new QueueMonitor/ED/Flowmon]
set cl [new Classifier/Hash/SrcDestFid 33]
$cl proc unknown-flow { src dst fid hash
www.eeworm.com/read/293183/8310146
m medianc.m
%MEDIANC Median combining classifier
%
% W = medianc(V)
% W = V*medianc
%
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the
% same classes and W is the median combiner: it selects
www.eeworm.com/read/293183/8310279
m prodc.m
%PRODC Product combining classifier
%
% W = prodc(V)
% W = V*prodc
%
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the
% same classes and W is the product combiner: it selects the
www.eeworm.com/read/411674/11233719
m contents.m
% Support Vector Machines.
%
% bsvm2 - Solver for multi-class BSVM with L2-soft margin.
% evalsvm - Trains and evaluates Support Vector Machines classifier.
% mvsvmclass - Majority votin
www.eeworm.com/read/111603/15509327
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/111603/15509376
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/111603/15509379
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a dag-svm multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/431675/8661718
m minc.m
%MINC Minimum combining classifier
%
% W = minc(V)
% W = V*minc
%
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the
% same classes and W is the minimum combiner: it selects the cla
www.eeworm.com/read/431675/8662092
m meanc.m
%MEANC Averaging combining classifier
%
% W = meanc(V)
% W = V*meanc
%
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the
% same classes and W is the mean combiner: it selects the c
www.eeworm.com/read/431675/8662162
m majorc.m
%MAJORC Majority combining classifier
%
% W = majorc(V)
% W = v*majorc
%
% If V = [V1,V2,V3,...] is a stacked set of classifiers trained for
% the same classes and W is the majority combiner: it se