Book cover

Rough set data analysis: A road to non-invasive knowledge discovery

Authors: Ivo Düntsch , Dept of Computer Science , Brock University , St Catharines, Ontario, L2S 3A1, Canada
Günther Gediga , Institut für Evaluation und Marktanalysen; Brinkstr. 19; D-49143 Jeggen, Germany,and Dept of Computer Science , Brock University , St Catharines, Ontario, L2S 3A1, Canada
Publisher Methodos Publishers
ISBN: 190328001X
Abstract: 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.
Download: Methodos Primers 2: Rough Set Data Analysis
Offered to the community with the kind permission by the authors and the publisher.
Resources: http://www.methodos.de/noninv/resources.html
Contents: 1 Introduction
2 Data models and model assumptions
3 Basic rough set data analysis
3.1 Fundamentals
3.2 Approximation quality
3.3 Information systems
3.4 Indiscernability relations
3.5 Feature reduction
3.6 Discernibility matrices and Boolean reasoning
3.7 Rules
3.8 Approximation quality
4 Rule significance
4.1 Significant and casual rules
4.2 Conditional significance
4.3 Sequential randomisation
5 Data discretisation
5.1 Classificatory discretisation
5.2 Discretisation of real valued attributes
6 Model selection
6.1 Dynamic reducts
6.2 Rough entropy measures
6.3 Entropy measures and approximation quality
7 Probabilistic granule analysis
7.1 The variable precision model
7.2 Replicated decision systems
7.3 An algorithm to find probabilistic rules
7.4 Unsupervised learning and nonparametric distribution estimates
8 Imputation
8.1 Statistical procedures
8.2 Imputation from known values
9 Beyond rough sets
9.1 Relational attribute systems
9.2 Noninvasive test theory
10 Epilogue

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