In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
In this paper, we examine the performance of frequent pattern mining algorithms on a modern processor. A detailed performance study reveals that even the best frequent pattern min...
Inductive learning systems have been successfully applied in a number of medical domains. Nevertheless, the effective use of these systems requires data preprocessing before apply...
Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
Abstract. In this study, we present methods for comparative visualization of DNA sequences in two dimensions. First, we illustrate a transformation of gene sequences into numerical...
Michail Vlachos, Bahar Taneri, Eamonn J. Keogh, Ph...