RE: How to improve the accuracy of classification of industrial d

Jin, Yaochu (Yaochu.Jin@alliedsignal.com)
Fri, 19 Mar 1999 20:23:04 +0100 (MET)

This might be due to overfitting. There are numerous papers in the neural
network community concerning learning and generalization. Regulariation
could be a good solution. From the fuzzy system point of view, maintaining
the interpretability/transparency of the fuzzy system during learning can
also improve generalization in some cases.

Yaochu Jin
----------
From: Peng YongHong
To: Multiple recipients of list
Subject: How to improve the accuracy of classification of industrial data?
Date: Wednesday, March 17, 1999 6:15PM

Dear all,

I doing a project for classifying a set of industrial data using BP or
neuro-fuzzy network. 120 input-outp data pair are used for training and
other 40 data are used for testing. Although the accuracy of training is
very good, the accuracy of classifying testing is not satisfactory,
since both the training data and test data are noisy.

Can anyone show me more information concerning this subject? Thanks in
advance.

--
------------------------------------------------------
Dr. PENG, YongHong
MEEM Dept., City Univ. of HongKong
Email: meyhpeng@cityu.edu.hk
-------------------------*-----------------------------------

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