Inhibitory rules in data analysis. A rough set approach
type: Item
instance of: scholarly article
title: Inhibitory rules in data analysis. A rough set approach
zbMATH Open document ID: 1157.68054
DOI: 10.1007/978-3-540-85638-2
author: Pawel Delimata
author: Mikhail Moshkov
author: Andrzej Skowron
author: Zbigniew Suraj
published in: Studies in Computational Intelligence
publication date: 2008-08-27T00:00:00Z
review text: This monograph is devoted to the theoretical and experimental study of decision and association rules. The most interesting part of the book is that it discusses an advanced mathematical analysis of problems and its rules. The rules are as well implemented with experiments. I am sure that this book will be very useful to researchers in the area of data mining and the analysis and design of concurrent systems. It will be useful for PhD students in their very first year of study.
reviewed by: Prabhat Kumar Mahanti
Mathematics Subject Classification ID: 68T01
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 68U35
Mathematics Subject Classification ID: 68-02
zbMATH DE Number: 5316809
zbMATH Keywords: association rules
zbMATH Keywords: information system
zbMATH Keywords: partial covers
zbMATH Keywords: decision rules
zbMATH Keywords: lazy classification
zbMATH Keywords: inhibitory decision rules
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-3-540-85638-2
OpenAlex ID: W3202817114
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description: scientific article; zbMATH DE number 5316809