How to deal with categorical variables in fuzzy modeling?

From: Wang, Liang (lxw@hnc.com)
Date: Fri Jul 06 2001 - 22:03:23 MET DST

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    I will appreciate very much receiving your thoughts on the
    following problem:

    Probelm statement:

    Build a fuzzy model (say a TSK model) using 20 variables, among
    which 10 are continuous numerical variables (e.g., balance,
    purchase amount etc) and 10 are categorical variables (e.g.,
    occupation, zip code, etc).

    Where is the difficulty?
    The difficulty is in the incorporation of the categorical
    variables into the model. There are various approaches to use
    categorical variables in traditional regression models such as
    linear and logistic, and these approaches can also be used
    in NN.

    But how to use them in fuzzy models? A possible solution may be
    to construct segmentations (like tree) using the categorical variables
    and then build models in each segmentation. But you will see that this
    approach is not practical when the number of categorical variables is
    large (say 10) and the numner of the items is large (such as zip code).

    Thanks,
    Liang Wang
    Sr. Staff Scientist
    HNC Software Inc.

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