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www.eeworm.com/read/232728/14184131
pdf mackay_-_information[1].theory,.inference.and.learning.algorithms.pdf
www.eeworm.com/read/227932/14406297
chm oreilly.learning.java.3rd.edition.may.2005.chm
www.eeworm.com/read/213285/15138226
pdf learning a rare event detection cascade by direct feature selection(2003).pdf
www.eeworm.com/read/190387/8444286
m hop_stor.m
function W=hop_stor(P)
% function W=hop_stor(P)
%
% performs the storage (learning phase) for a Hopfield network
%
% W - weight matrix
% P - patterns to be stored (column wise matrix)
%
% Hugh
www.eeworm.com/read/289680/8535072
bbl manual.bbl
\begin{thebibliography}{}
\bibitem[Boser et~al., 1992]{Boser1992}
Boser, B., Guyon, I., and Vapnik, V.~N. (1992).
\newblock A training algorithm for optimal margin classifiers.
\newblock In {\em
www.eeworm.com/read/188280/8552200
bbl manual.bbl
\begin{thebibliography}{}
\bibitem[Boser et~al., 1992]{Boser1992}
Boser, B., Guyon, I., and Vapnik, V.~N. (1992).
\newblock A training algorithm for optimal margin classifiers.
\newblock In {\em
www.eeworm.com/read/431675/8662269
m prex2.m
%PREX2 PRTOOLS example, plot learning curves of classifiers
help prex2
pause(1)
echo on
% set desired learning sizes
learnsize = [3 5 10 15 20 30];
% Generate Highleyman's classes
A = gend
www.eeworm.com/read/386950/8716555
m dataforc45.m
%DataForC45.m
%Shiliang Sun, Apr. 8, 2007.
%The data are constructed from Table 3.2 of Mitchell's book:
%Machine Learning.
Traindata=[
7 1 1 1 2
7 1 1 2 2
8 1 1 1 1
www.eeworm.com/read/183443/9158902
bbl manual.bbl
\begin{thebibliography}{}
\bibitem[Boser et~al., 1992]{Boser1992}
Boser, B., Guyon, I., and Vapnik, V.~N. (1992).
\newblock A training algorithm for optimal margin classifiers.
\newblock In {\em