Clustering of large data bases is an important research area with a large variety of applications in the data base context. Missing in most of the research efforts are means for g...
Alexander Hinneburg, Daniel A. Keim, Markus Wawryn...
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. FuzzyUCS combines the generalization capabilities of UCS w...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Abstract. In this paper we explore the use of the Voxel-based Morphometry (VBM) detection clusters to guide the feature extraction processes for the detection of Alzheimer's d...
Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...