Classification and Clustering in a Fuzzy Environment

2012
Ludmila Aleksejeva, Oļegs Užga-Rebrovs, Arkādijs Borisovs

This monograph is devoted to popular intelligent data processing techniques - classification and clustering. Algorithms execution principles are described both in a crisp and in a fuzzy environment. The algorithms designed for solving classification tasks in a fuzzy environment are based both on rules and decision trees. To demonstrate their execution principles, a case study is provided for each algorithm. The book will be helpful for intelligent data processing specialists and students of Computer Science and Information Technology programme.

Keywords
Data mining, fuzzy classification, fuzzy decision tree, fuzzy cluster, fuzzy probabilistic gain

Aleksejeva, L., Užga-Rebrovs, O., Borisovs, A. Classification and Clustering in a Fuzzy Environment. Rīga: Rīgas Tehniskā universitāte, 2012. 248 p. ISBN 978-9934-10-300-1.

Publication language
Latvian (lv)