Fuzzy Approach to Hierarchical Clustering

In this book we tried to extend the possibilities of hierarchical clustering methods to manipulate with fuzzy data both during preparing and clustering of data.The main aim was to apply some results of fuzzy sets theory and to develop new elements of hierarchical agglomerative clustering alforithms especially focused on manipulating with fuzzy data. The main goal consisted of the following parts - to prepare the fuzzy data for cluster analysis, to extend the definition of object dissimilarity for the case of fuzzy objects; to realize clustering of fuzzy data, to search of Tolerance coefficient for Definite hierarchical agglomerative clustering method and to find Partition optimality coefficient by means of fuzzy c-means algorithm.

Autorentext

Martin Mal ík - Vice-dean of the Pedagogical Faculty, works atthe Department of Education and Adult Education, PedagogicalFaculty, University of Ostrava. In terms of the research hefocuses on the problems of school evaluation with a focus onelectronic testing and educational technologies in relation tothe development of human resources.