Re: Assumption free (neuro)-fuzzy modeling????

Robert Dodier (dodier@colorado.edu)
Mon, 16 Nov 1998 05:11:49 +0100 (MET)

In article <72hj4s$sn0$1@news.tudelft.nl>, Sjonnie <Sjonnie@holland.nl> wrote:

> I have a paper here of Fang and Chen.
>
> They say: "Fuzzy modeling, ... , is not only assumption free but also rubust
> to deviations, even outliers. "
>
> What does this mean?
> Do you agree?
[...]

This statement appears to be a dramatic overstatement, inserted into the
paper for rhetorical purposes.

Every modeling technique makes assumptions about the process that is
being modeled. It is important to understand what those assumptions
are, instead of dismissing the assumptions as unimportant.

For example, every type of modeling approach with which I am familiar
assumes that the data available for building the model are representive
of data generated by the process. If the process begins to generate
substantially different data, the model will break down.

Actually, I would not want a modeling technique completely free of
assumptions. The trick is to make the assumptions match your knowledge
of how the process works -- that is, assumptions are an opportunity
to build your knowledge into the model.

Regards,
Robert Dodier

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