Clustering and Data Analysis Toolbox

The toolbox provides four categories of functions.

Nowadays due to the yearly multiplying data comes always the claim for useful methods and algorithms that make the processing of these data easier. For the solution of this problem data mining tools come into existence, to which the clustering algorithms belong. At the Department of Process Engineering of the University of Veszprem much research has been done on the clustering algorithms, many articles, publications and an MSc theme were published dealing with this topic. To unite all these information and knowledge a "Clustering and Data Analysis Toolbox" was needful. The purpose of this work was to compile a continuously extensible, standard tool, which is useful for any MATLAB user for one's aim. In Chapter 1 of the downloadable related documentation one can find a theoretical introduction containing the theory of the algorithms, the definition of the validity measures and the tools of visualization, which help to understand the programmed MATLAB files. Chapter 2 deals with the exposition of the files and the description of the particular algorithms, and they are illustrated with simple examples, while in Chapter 3 the whole Toolbox is tested on real data sets during the solution of three clustering problems: comparison and selection of algorithms; estimating the optimal number of clusters; and examining multidimensional data sets.