Hi

I recently started playing with the nnet package and the IRIS dataset. I
would love to hear from anyone that has used this package to build a
predictive model in finance. Specifically, I would like to get some pointers
on the modeling aspects i.e. normalization of inputs, directional predictors
vs. magnitude predictors, neural networks vs. kernel regression etc. Any
other pointers on books / articles would be great as well.

Thanks
Mike

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