You are right there is a pdf file which describes the function. But let tell you where I am coming from.

Just to test if a neural network will work better than a ordinary least square regression, I created a dataset with one dependent variable and 6 other independent variables. Now I had deliberately created the dataset in such manner that we have an excellent regression model. Eg: Y = b0 + b1*x1 + b2*x2 + b3*x3.. + b6*x6 + e
where e is normal random variable. Naturally any statistical analysis system running regression would easily predict the values of b1, b2, b3, ..., b6 with around 30-40 observations.

I fed this data into a Neural network (3 hidden layers with 6 neurons in each layer) and trained the network. When I passed the input dataset and tried to get the predictions, all the predicted values were identical! This confused me a bit and was wondering whether my understanding of the Neural Network was wrong.

Have you ever faced anything like it?

Regards,
Indrajit



________________________________
From: "markleeds@verizon.net" <markleeds@verizon.net>

Sent: Wednesday, May 27, 2009 7:54:59 PM
Subject: Re: [R] Neural Network resource

Hi: I've never used that package but most likely there is a  AMORE vignette that shows examples and describes the functions.
it should be on the same cran  web page where the package resides, in pdf form.






Hi All,

I am trying to learn Neural Networks. I found that R has packages which can help build Neural Nets - the popular one being AMORE package. Is there any book / resource available which guides us in this subject using the AMORE package?

Any help will be much appreciated.

Thanks,
Indrajit

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