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/282250/9108618
cpp classifiers.cpp
//====
// Classifiers.cpp
// - implements a few methods defined in Classifiers.hpp
// Notes
// - this package is for experiment and demo purposes only,
// because it operates on full feature-documen
www.eeworm.com/read/183445/9158642
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/183445/9158654
asv ls_svm2.asv
% 支持向量机最小二乘算法(LS-SVM)--可用于分类和回归???
% function [ output_args ] = SvmLs( input_args )
clc
clear
close all
m = 4; % 样本维数
TrainSample = [1+rand(m,5),2+rand(m,5),3+rand(m,5),4+rand(m,5)];
TrainTa
www.eeworm.com/read/183445/9158705
m code.m
function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args)
% Encode and decode a multi-class classification task into multiple binary cl
www.eeworm.com/read/183445/9158783
asv code.asv
function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args)
% Encode and decode a multi-class classification task into multiple binary cl
www.eeworm.com/read/179898/9331875
h classify.h
/*--------------------------------------------------------------------------
@COPYRIGHT :
Copyright 1997, Vasken Kollokian,
McConnell Brain Imaging Centre,
www.eeworm.com/read/179071/9374811
tcl example.tcl
#
# Copyright (c) 2001-2005 Paolo Losi (p.losi@hypersonic.it)
# Alexander Sayenko (sayenko@cc.jyu.fi)
#
# All rights reserved
#
# This program is free software; you can redistr
www.eeworm.com/read/374698/9388836
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/374698/9388841
asv ls_svm2.asv
% 支持向量机最小二乘算法(LS-SVM)--可用于分类和回归???
% function [ output_args ] = SvmLs( input_args )
clc
clear
close all
m = 4; % 样本维数
TrainSample = [1+rand(m,5),2+rand(m,5),3+rand(m,5),4+rand(m,5)];
TrainTa
www.eeworm.com/read/374698/9388887
m code.m
function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args)
% Encode and decode a multi-class classification task into multiple binary cl