代码搜索：Learning
找到约 5,352 项符合「Learning」的源代码
代码结果 5,352
www.eeworm.com/read/362246/10010387
m~ contents.m~
% Algorithms learning linear classifiers from finite vector sets.
%
% ekozinec - Kozinec's algorithm for eps-optimal separating hyperplane.
% ekozinec2 - Kozinec's algorithm for eps-optimal separ
www.eeworm.com/read/280595/10312291
m~ contents.m~
% Algorithms learning linear classifiers from finite vector sets.
%
% ekozinec - Kozinec's algorithm for eps-optimal separating hyperplane.
% ekozinec2 - Kozinec's algorithm for eps-optimal separ
www.eeworm.com/read/351797/10609758
bib manual.bib
@misc{Bay1999,
author = "Bay, S. D.",
title = "The {UCI} {KDD} Archive
$[$\texttt{http://kdd.ics.uci.edu/}$]$",
howpublished = "University of California, D
www.eeworm.com/read/349842/10797005
txt preprocessing.txt
ADDC@Number of partitions:@4@S
AGHC@Number of partitions, Distance:@[4, 'min']@S
BIMSEC@Num of partitions, Nattempts:@[4, 1]@S
Competitive_learning@Number of partitions, eta:@[4, .01]@S
Determinis
www.eeworm.com/read/299459/7850792
m~ contents.m~
% Algorithms learning linear classifiers from finite vector sets.
%
% ekozinec - Kozinec's algorithm for eps-optimal separating hyperplane.
% ekozinec2 - Kozinec's algorithm for eps-optimal separ
www.eeworm.com/read/398324/7994346
bib manual.bib
@misc{Bay1999,
author = "Bay, S. D.",
title = "The {UCI} {KDD} Archive
$[$\texttt{http://kdd.ics.uci.edu/}$]$",
howpublished = "University of California, D
www.eeworm.com/read/398324/7994488
bib manual.bib
@misc{Bay1999,
author = "Bay, S. D.",
title = "The {UCI} {KDD} Archive
$[$\texttt{http://kdd.ics.uci.edu/}$]$",
howpublished = "University of California, D
www.eeworm.com/read/245176/12813244
bib manual.bib
@misc{Bay1999,
author = "Bay, S. D.",
title = "The {UCI} {KDD} Archive
$[$\texttt{http://kdd.ics.uci.edu/}$]$",
howpublished = "University of California, D
www.eeworm.com/read/140850/13059572
bib manual.bib
@misc{Bay1999,
author = "Bay, S. D.",
title = "The {UCI} {KDD} Archive
$[$\texttt{http://kdd.ics.uci.edu/}$]$",
howpublished = "University of California, D
www.eeworm.com/read/321501/13403954
txt readme.txt
人工神经网络实验系统(BP网络) V1.0 Beta
零.说在前面的一番话
大家好，这个程序是我自己做的，为了学习的方便和用于研究目的。
其运用了人工神经网络中的前向网终的BP网络的理论，还结合了Hebb学
习规则，使其具有一定的学习、自适应和分辩能力。
本来，只做了个感知器的模型，后将多个感知器用BP网络连结，
做成一个"人工大脑"。对这 ...