@inproceedings{4fa82520c1bc4992b2bc05b1f09c4203,
title = "Fully unsupervised clustering in nonlinearly separable data using intelligent Kernel K-Means",
abstract = "Intelligent Kernel K-Means is a fully unsupervised clustering technique. This technique is developed by combining Intelligent K-Means and Kernel K-Means. Intelligent Kernel K-Means used to cluster kernel matrix without any information about the number of clusters. The goal of this research is to evaluate the performance of Intelligent Kernel K-Means for clustering nonlinearly separable data. Various artificial nonlinearly separable data are used in this experiment. The best result is the clustering often ring datasets. It produces Adjusted Rand Index (ARI) = 1.",
keywords = "K-Means, clustering, fully unsupervised clustering, intelligent Kernel K-Means",
author = "Teny Handhayani and Ito Wasito",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014 ; Conference date: 18-10-2014 Through 19-10-2014",
year = "2014",
month = mar,
day = "23",
doi = "10.1109/ICACSIS.2014.7065891",
language = "English",
series = "Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "450--453",
booktitle = "Proceedings - ICACSIS 2014",
address = "United States",
}