Netlab

Pattern analysis toolbox.

Description

The Netlab toolbox is designed to provide the central tools necessary for the simulation of theoretically well founded neural network algorithms and related models for use in teaching, research and applications development. It contains many techniques which are not yet available in standard neural network simulation packages.

The principles behind the toolbox are more important than simply compiling lists of algorithms. Data analysis and modelling methods should not be used in isolation; all parts of the toolbox interact in a coherent way, and implementations of standard pattern recognition techniques (such as linear regression and K-nearest-neighbour classifiers) are provided so that they can be used as benchmarks against which more complex algorithms can be evaluated. This interaction allows researchers to develop new techniques by building on and reusing existing software, thus reducing the effort required and increasing the robustness and usability of the new tools.

An accompanying text book, Netlab: Algorithms for Pattern Recognition written by Ian Nabney is published by Springer in their series Advances in Pattern Recognition: the ISBN number is 1-85233-440-1. More information can be found at http://www.ncrg.aston.ac.uk and http://www.mathworks.com/support/books/book4368.jsp.

• MATLAB release: MATLAB 6.1 (R12.1)

Other Files

conffig.m,
confmat.m,
conjgrad.m,
consist.m,
Contents.m,
datread.m,
datwrite.m,
dem2ddat.m,
demard.m,
demev1.m,
demev2.m,
demev3.m,
demgauss.m,
demglm1.m,
demglm2.m,
demgmm1.m,
demgmm2.m,
demgmm3.m,
demgmm4.m,
demgmm5.m,
demgpard.m,
demgp.m,
demgpot.m,
demgtm1.m,
demgtm2.m,
demhint.m,
demhmc1.m,
demhmc2.m,
demhmc3.m,
demkmn1.m,
demknn1.m,
demmdn1.m,
demmet1.m,
demmlp1.m,
demmlp2.m,
demnlab.m,
demns1.m,
demolgd1.m,
demopt1.m,
dempot.m,
demprgp.m,
demprior.m,
demrbf1.m,
demsom1.m,
demtrain.m,
dist2.m,
eigdec.m,
errbayes.m,
evidence.m,
fevbayes.m,
gauss.m,
gbayes.m,
glmderiv.m,
glmerr.m,
glmevfwd.m,
glmfwd.m,
glmgrad.m,
glmhess.m,
glminit.m,
glm.m,
glmpak.m,
glmtrain.m,
glmunpak.m,
gmmactiv.m,
gmmem.m,
gmminit.m,
gmm.m,
gmmpak.m,
gmmpost.m,
gmmprob.m,
gmmsamp.m,
gmmunpak.m,
gpcovarf.m,
gpcovar.m,
gpcovarp.m,
gperr.m,
gpfwd.m,
gpgrad.m,
gpinit.m,
gp.m,
gppak.m,
gpunpak.m,
gradchek.m,
graddesc.m,
gsamp.m,
gtmem.m,
gtmfwd.m,
gtminit.m,
gtmlmean.m,
gtmlmode.m,
gtm.m,
gtmmag.m,
gtmpost.m,
gtmprob.m,
hbayes.m,
hesschek.m,
hintmat.m,
hinton.m,
histp.m,
hmc.m,
kmeans.m,
knnfwd.m,
knn.m,
linef.m,
linemin.m,
mdn2gmm.m,
mdndist2.m,
mdnerr.m,
mdnfwd.m,
mdngrad.m,
mdninit.m,
mdn.m,
mdnpak.m,
mdnpost.m,
mdnprob.m,
mdnunpak.m,
metrop.m,
minbrack.m,
mlpbkp.m,
mlpderiv.m,
mlperr.m,
mlpevfwd.m,
mlpfwd.m,
mlpgrad.m,
mlphdotv.m,
mlphess.m,
mlphint.m,
mlpinit.m,
mlp.m,
mlppak.m,
mlpprior.m,
mlptrain.m,
mlpunpak.m,
netderiv.m,
neterr.m,
netevfwd.m,
netgrad.m,
nethess.m,
netinit.m,
netopt.m,
netpak.m,
netunpak.m,
olgd.m,
pca.m,
plotmat.m,
ppca.m,
quasinew.m,
rbfbkp.m,
rbfderiv.m,
rbferr.m,
rbfevfwd.m,
rbffwd.m,
rbfgrad.m,
rbfhess.m,
rbfjacob.m,
rbf.m,
rbfpak.m,
rbfprior.m,
rbfsetbf.m,
rbfsetfw.m,
rbftrain.m,
rbfunpak.m,
rosegrad.m,
rosen.m,
scg.m,
somfwd.m,
som.m,
sompak.m,
somtrain.m,
somunpak.m,
mdnnet.mat,
netlogo.mat,
oilTrn.dat,
oilTst.dat,
xor.dat,
LICENSE

[Narayanaswamy M]

please send the tutorials on gaussian mixture model to my mail.

this site is very good

[Arshia Gerami]

 

[subrata bose]

could u please send a tutorial on netlab

[Girija Chetty]

very helpful compilation of files

[ASHOK SHARMA]

GOODONE

[ashok sharma]

really helpful last download did not fully work

[Dale Clifford]

Outstanding tool for use in addition to Matlabs nnet toolbox. Netlab incorporates concepts from baysien conditional type models into nnets. Reader particularly liked and found the parts from data sampling and optimization useful. Material bridges some of the gap between statistical data anaylsis and the control system approach used by the Matlab toolbox.

[Lawrence Ng]

Hi, I am trying to load netlab into Matlab ver 13 but the software does not recognise the commands used in netlab. Can someone help me....tks

[messaoud bouakkaz]

 

[Ade Idowu]

I have used NetLab for for doing preliminary research and general benchmarking of Neural Network ideas. I find the toolbox very useful, especially when it is used with the accompanying text book.