Neural Net Classification #2

I'm experimenting with using wavelets for feature extraction from a
data time series and then classifying based on the extracted features
into one of two categories. My data set consists of 75% sample of
Type I and 25% of Type II. I've tried both a Feed Forward ANN and
LVQ. Neither approach have produced good results on out of training
sample sets, i.e., low identification rate of type II.

I would appreciate any advice on the following:

1. Preprocessing - Should I preprocess the wavelet coefficient
inputs in any manner? (I'm compressing the data time series to reduce
the number of wavelet coefficients presented to the network)
2. Training - Matlab does not appear to support
early-stopping/validation for LVQ. I would appreciate any advice on
training parameters for the LVQ to improve generalization. (I do use
early stopping for the FF ANN)

Thanks is advance.
adorenbaum (30)
12/16/2004 12:19:41 AM
comp.soft-sys.matlab 211264 articles. 25 followers. lunamoonmoon (257) is leader. Post Follow

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