@inproceedings{e47039fd99794f2da2588fdb8d773be3,
title = "Robust fuzzy clustering algorithms",
abstract = "A class of fuzzy clustering algorithms based on a recently introduced 'noise cluster' concepts is proposed. A 'noise prototype' is defined such that it is equi-distant to all the points in the data-set. This allows for detection of clusters amongst data with or without noise. It is shown that this concept is applicable to all the generalizations of fuzzy or hard k-means algorithms. Various applications are also considered. Application of this concept to a variety of regression problems is also considered. It is shown that the results of this approach are comparable to many robust regression techniques. The paper concludes with a summary and directions for future work.",
author = "Dave, {Rajesh N.}",
year = "1993",
language = "English (US)",
isbn = "0780306155",
series = "1993 IEEE International Conference on Fuzzy Systems",
publisher = "Publ by IEEE",
pages = "1281--1286",
booktitle = "1993 IEEE International Conference on Fuzzy Systems",
note = "Second IEEE International Conference on Fuzzy Systems ; Conference date: 28-03-1993 Through 01-04-1993",
}