On the usefulness of fuzzy SVMs and the extraction of fuzzy rules from SVMs
Christian Moewes, Rudolf Kruse
Available Online August 2011.
- https://doi.org/10.2991/eusflat.2011.46How to use a DOI?
- Classification, fuzzy rule-based classifiers, fuzzy SVM, SVM
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Christian Moewes AU - Rudolf Kruse PY - 2011/08 DA - 2011/08 TI - On the usefulness of fuzzy SVMs and the extraction of fuzzy rules from SVMs PB - Atlantis Press SP - 943 EP - 948 SN - 1951-6851 UR - https://doi.org/10.2991/eusflat.2011.46 DO - https://doi.org/10.2991/eusflat.2011.46 ID - Moewes2011/08 ER -