Rough Set Data Analysis: A Road To Non-invasive Knowledge Discovery

E-Book Overview

This is not the first book on rough set analysis and certainly not the first book on knowledge discovery algorithms, but it is the first attempt to do this in a non-invasive way. In this book the authors present an overview of the work they have done in the past seven years on the foundations and details of data analysis. It is a look at data analysis from many different angles, and the authors try not to be biased for - or against - any particular method. This book reports the ideas of the authors, but many citations of papers on Rough Set Data Analysis in knowledge discovery by other research groups are included as well.

E-Book Content

`b ,6%1 ; Günther Gediga teaches in the Faculty of Psychology at the Universität Osnabrück. His main interests are the mathematical foundations of Psychometrics and Data Analysis, a task which needs a precise description of basic mathematical ideas such as those presented in this book. About the authors: Ivo Düntsch is Professor for Computing Science at the Faculty of Informatics of the University of Ulster. His main interests are algebraic logic and the modelling of knowledge under incomplete information. About the book This is not the first book on rough set analysis and certainly not the first book on knowledge discovery algorithms, but it is the first attempt to do this in a non-invasive way. In this book the authors present an overview of the work they have done in the past seven years on the foundations and details of data analysis. It is a look at data analysis from many different angles, and the authors try not to be biased for – or against – any particular method. This book reports the ideas of the authors, but many citations of papers on Rough Set Data Analysis in knowledge discovery by other research groups are included as well. Methoδ δos Primers Series: The aim of this series is to make available concise introductions to topics in Methodology, Evaluation, Psychometrics, Statistics, Data Analysis at an affordable price. Each volume is written by experts in the field, guaranteeing a high scientific standard. 2 δ Düntsch & Gediga Rough set data analysis: A road to non-invasive data analysis δos Methoδ A road to non-invasive knowledge discovery Rough set data analysis Ivo Düntsch & Günther Gediga Primers Series, Vol. 2 Metho os Primers, Vol. 2 The aim of the Metho os Primers series is to make available concise introductions to topics in Methodology, Evaluation, Psychometrics, Statistics, Data Analysis at an affordable price. Each volume is written by experts in the field, guaranteeing a high scientific standard. Metho os Publishers (UK) Metho  os Verlag (D) Rough set data analysis: A road to non-invasive knowledge discovery Ivo Düntsch Günther Gediga School of Information and Software Engineering FB Psychologie / Methodenlehre University of Ulster Universität Osnabrück Newtownabbey, BT 37 0QB, N.Ireland 49069 Osnabrück, Germany [email protected] [email protected] First published in 2000 by Metho os Publishers (UK), 24 Southwell Road Bangor, BT20 3AQ  c 2000 by Ivo Düntsch and Günther Gediga. ISBN 190328001X A CIP record for this book is available from the British Library. Ivo Düntsch and Günther Gediga’s right to be identified as the authors of this work has been asserted in accordance with the Copyright Design and Patents Act 1988. All rights reserved. No p
You might also like

Lexikon Der Informatik
Authors: Peter Fischer , Peter Hofer    155    0


Parallel And Distributed Logic Programming
Authors: Bhattacharya A. , Konar A. , Mandal A.    187    0


Network Analysis: Methodological Foundations
Authors: Ulrik Brandes , Thomas Erlebach (auth.) , Ulrik Brandes , Thomas Erlebach (eds.)    178    0



Functional Programming
Authors: Fokker J.    174    0


Scientific Visualization: The Visual Extraction Of Knowledge From Data
Authors: Georges-Pierre Bonneau , Thomas Ertl , Gregory M. Nielson    152    0



The Comprehensive Latex Symbol List
Authors: Pakin S.    170    0



Adobe Golive 6.0
Authors: Adobe Creative Team    129    0