@inproceedings{0417cd49ccaa49c180d4f118d24c5f54,
title = "Classification based on incremental fuzzy (1 + p)-means clustering",
abstract = "Fuzzy clustering is often applied to determine the rules of the fuzzy rule-based classifiers (usually the antecedents only). In this work a new fuzzy clustering approach is proposed for such a purpose. The idea consists in alternating clustering of the objects from two classes with the prototypes obtained after the previous clustering not allowed to move during the current clustering. As a result each clustering provides newlocation of a single prototype. The classification quality obtained by the fuzzy rule-based classifier using the proposed clustering was compared with the Lagrangian SVM method on several benchmark databases.",
keywords = "Clustering, Fuzzy rule-based classification",
author = "Michal Jezewski and Leski, \{Jacek M.\} and Robert Czabanski",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 4th International Conference on Man{\textendash}Machine Interactions, ICMMI 2015 ; Conference date: 06-10-2015 Through 09-10-2015",
year = "2016",
doi = "10.1007/978-3-319-23437-3\_48",
language = "English",
isbn = "9783319234366",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "563--572",
editor = "Tadeusz Czach{\'o}rski and Aleksandra Gruca and Agnieszka Brachman and Stanis{\l}aw Kozielski and Tadeusz Czach{\'o}rski",
booktitle = "Man{\textendash}Machine Interactions - 4th International Conference on Man{\textendash}Machine Interactions, ICMMI 2015",
address = "Germany",
}