Type-2 Fuzzy Classifier Ensembles for Text Entailment
Asli Celikyilmaz1, I. Burhan Turksen
1University of California, Berkeley
Available Online December 2008.
- 10.2991/jcis.2008.11How to use a DOI?
- type-2 fuzzy sets, classifier ensembles, fuzzy c-classification.
This paper presents a new Type-2 Fuzzy Classifier ensemble, which enables to model parameter uncertainties by charac-terizing the fuzzy sets with secondary membership values. We use fuzzy clus-tering method to characterize primary membership values and genetic algorithm to approximate secondary membership grades. Furthermore, a weighing algo-rithm is used for a non-complex reduction for reasoning. We use transductive rea-soning, instead of inductive reasoning, to develop a local model for every new vec-tor, based on a nearness criterion vectors from the given database. It is shown that the method can improve classifier system modeling performance in comparison to well-known methods.
- © 2008, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Asli Celikyilmaz AU - I. Burhan Turksen PY - 2008/12 DA - 2008/12 TI - Type-2 Fuzzy Classifier Ensembles for Text Entailment BT - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008) PB - Atlantis Press SP - 66 EP - 72 SN - 1951-6851 UR - https://doi.org/10.2991/jcis.2008.11 DO - 10.2991/jcis.2008.11 ID - Celikyilmaz2008/12 ER -