title: |
On the usefulness of fuzzy SVMs and the extraction of fuzzy rules from SVMs |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| pages: | 943 - 948 | |
DOI: |
To be assigned soon (how to use a DOI) | |
author(s): |
Christian Moewes, Rudolf Kruse |
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publication date: |
July 2011 |
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keywords: |
Classification, fuzzy rule-based classifiers, fuzzy SVM, SVM |
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abstract: |
In this paper we reason about the usefulness of two
recent trends in fuzzy methods in machine learning.
That is, we discuss both fuzzy support vector machines (FSVMs) and the extraction of fuzzy rules
from SVMs. First, we show that an FSVM is identical to a special type of SVM. Second, we categorize and analyze existing approaches to obtain fuzzy
rules from SVMs. Finally, we question both trends
and conclude with more promising alternatives. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |