This monograph is devoted to theoretical and experimental study of partial reductsandpartialdecisionrulesonthebasisofthestudyofpartialcovers. The use of partial (approximate) reducts and decision rules instead of exact ones allowsustoobtainmorecompactdescriptionofknowledgecontainedindecision tables,andtodesignmorepreciseclassi?ers. Weconsideralgorithmsforconstructionofpartialreductsandpartialdecision rules,boundsonminimalcomplexityofpartialreductsanddecisionrules,and algorithms for construction of the set of all partial reducts and the set of all irreducible partial decision rules. We discuss results of numerous experiments with randomly generated and real-life decision tables. These results show that partial reducts and decision rules can be used in data mining and knowledge discoverybothforknowledgerepresentationandforprediction. Theresultsobtainedinthe monographcanbe usefulforresearchersinsuch areasasmachinelearning,dataminingandknowledgediscovery,especiallyfor thosewhoareworkinginroughsettheory,testtheoryandLAD(LogicalAnalysis ofData). The monographcan be usedunder the creationofcoursesforgraduates- dentsandforPh. D. studies. An essential part of software used in experiments will be accessible soon in RSES-RoughSetExplorationSystem(InstituteofMathematics,WarsawU- versity,headofproject-ProfessorAndrzejSkowron). We are greatly indebted to Professor Andrzej Skowron for stimulated d- cussionsand varioussupportof ourwork. We aregratefulto ProfessorJanusz Kacprzykforhelpfulsuggestions. Sosnowiec,Poland MikhailJu. Moshkov April2008 MarcinPiliszczuk BeataZielosko Contents Introduction...1 1 PartialCovers,ReductsandDecisionRules ...7 1. 1 PartialCovers...8 1. 1. 1 MainNotions...8 1. 1. 2 Known Results...9 1. 1. 3 PolynomialApproximateAlgorithms...10 1. 1. 4 Bounds on C (?)Based on Information about min GreedyAlgorithm Work...13 1. 1. 5 UpperBoundon C (?)...17 greedy 1. 1. 6 Covers fortheMostPartofSetCoverProblems...18 1. 2 PartialTests and Reducts...22 1. 2. 1 MainNotions...22 1. 2. 2Relationships betweenPartialCovers and Partial Tests...23 1. 2. 3 PrecisionofGreedyAlgorithm...24 1. 2. 4 PolynomialApproximateAlgorithms...25 1. 2. 5 Bounds on R (?)Based on Information about min GreedyAlgorithm Work...26 1. 2. 6 UpperBoundon R (?)...28 greedy 1. 2. 7 Tests fortheMostPartofBinaryDecisionTables...29 1. 3 PartialDecision Rules...
Les mer
This book covers the theoretical and experimental study of partial reducts and partial decision rules on the basis of the study of partial covers. It details the results of numerous experiments with randomly generated and real-life decision tables.
Les mer
Partial Covers, Reducts and Decision Rules.- Partial Covers, Reducts and Decision Rules with Weights.- Construction of All Irreducible Partial Covers, All Partial Reducts and All Irreducible Partial Decision Rules.- Experiments with Real-Life Decision Tables.- Universal Attribute Reduction Problem.
Les mer

This monograph is devoted to theoretical and experimental study of partial reducts and partial decision rules on the basis of the study of partial covers. The use of partial (approximate) reducts and decision rules instead of exact ones allows us to obtain more compact description of knowledge contained in decision tables, and to design more precise classifiers. Algorithms for construction of partial reducts and partial decision rules, bounds on minimal complexity of partial reducts and decision rules, and algorithms for construction of the set of all partial reducts and the set of all irreducible partial decision rules are considered. The book includes a discussion on the results of numerous experiments with randomly generated and real-life decision tables. These results show that partial reducts and decision rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction.

The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and LAD (Logical Analysis of Data). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies.

Les mer
Latest research on Partial covers, reducts and decision rules in rough sets
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

Produktdetaljer

ISBN
9783642088599
Publisert
2010-10-28
Utgiver
Vendor
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet