Data mining. Development and application of robust methods for entreprise economics applications (Q2703378)

Knowledge discovery in databases is becoming a more and more important part of business intelligence. This volume is concerned with the development and application of robust methods for data mining.NEWLINENEWLINENEWLINEChapters 2 and 3 discuss various methods in detail, while chapter 4 is concerned with data preprocessing and pattern postprocessing. Chapter 5 gives five case studies showing the use of the proposed methods in practice.NEWLINENEWLINENEWLINEThe work is in large parts a condensed version of Thomas Wittmann, Wissensentdeckung in Datenbanken mit adaptiven Regelsystemen, volume 1 in the same series, but also with several extensions: chapter 2 treats graph theoretic models of dependency analysis, namely the MIM program, the K2-algorithm and the Tetrad-algorithm, and chapter 5 has two more case studies, now including the application of dependency analysis.NEWLINENEWLINENEWLINEChapter 3 first gives short introductions into methods from artificial intelligence like neural networks, decision trees and rule induction. Then some systems for neuro-fuzzy systems are introduced and compared, including NEFCLASS and SIEFUZZY.