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/316604/13520542
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/312163/13617563
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/134901/5891552
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/128684/5980344
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/359185/6352606
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/493206/6398617
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/483114/6609727
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/410924/11265092
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/409227/11340050
m fun_fnn_noise_emc.m
function [FNN_out,m,sigma,w4,error]=Fun_FNN_noise_EMC(x,m,sigma,w4,afaw4,afam,afasig,learning,r,totel,t,snr)
%%%%%%%%%%%%%%====================================$$$$$$$$$$$$$$$$$$$$$$$$
www.eeworm.com/read/153218/12051691
m plot_7_8.m
% make figure 7.8
Z3=zeros(4,491);
t=66;
for i=1:4,
eval(['load run' num2str(i)]);
z=sum(real(E).^2,2);
[y ind]=sort(z);
newE=E(ind,:);
Z3(i,:)=sum((real(newE(1:400-t,:)).^2))/(