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From: Greg Heath <heath@alumni.brown.edu>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Pattern Classification using Neural Network ( newff)
Date: Sun, 8 Nov 2009 03:18:43 -0800 (PST)
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On Nov 8, 5:42 am, Greg Heath <he...@alumni.brown.edu> wrote:
> On Nov 2, 8:45 pm, "Kishore " <kishore3...@yahoo.co.in> wrote:
>
> > Hello,
>
> > I am trying to classify a 4 class problem (each class has
> > 20 features ) using neural network.
> > So, in order to reduce the complexity, i used newff function to
> > get the weights.
>
> > The  problem is i am not very familiar with newff function usage
> > ( the samples are not classified properly- same sample set is being
> > classified welll using k nearest neighbour and bayesian techniques).
>
> > It would be great if i can get feed back on the usage of  this
> > newff sequence.
>
> > %%%%%%%%
>
> > net = newff(training_data',group',no_hiddenLayer);
>
> help newff
> doc newff
>
> You have accepted the PURELIN output default. For classification,
> LOGSIG is superior. The output then represents the posterior
> probability (conditional on the input) for class "1".

You have accepted the PURELIN output default. For classification,
LOGSIG is superior. The ith output then represents the posterior
probability (conditional on the input) for class "i".

Hope this helps.

Greg