In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
Measuring the similarity between clusterings is a classic problem with several proposed solutions. In this work we focus on measures based on coassociation of data pairs and perfor...
Algorithms for clustering web search results have to be efficient and robust. Furthermore they must be able to cluster a dataset without using any kind of a priori information, s...
Steven Schockaert, Martine De Cock, Chris Cornelis...
Abstract. We apply the Unsupervised Niche Clustering (UNC), a genetic niching technique for robust and unsupervised clustering, to the intrusion detection problem. Using the normal...