Titlebook: Rough Set Methods and Applications; New Developments in Lech Polkowski,Shusaku Tsumoto,Tsau Y. Lin Book 2000 Springer-Verlag Berlin Heidel

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1434-9922 d ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.978-3-662-00376-3978-3-7908-1840-6Series ISSN 1434-9922 Series E-ISSN 1860-0808

Kidney-Failure

Regularity Analysis and its Applications in Data Miningful tool not only for concept description. It is also indispensable for various applications like classification or decomposition. In this Chapter we present also the applications of data regularity to three basic problems of data mining: classification, data description and data decomposition.

噴油井

Statistical Techniques for Rough Set Data Analysisthe — stated or unstated — model assumptions. The question arises, whether there is a step in the modelling process which is informative for the researcher and, at the same time, does not require additional assumptions about the data. To make this clearer, we follow [9] in assuming that a data model consists of

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Book 2000y or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant

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Introducing the Bookowron: . (1998) were presented to the research community (cf. [A]2, [A]3, [A]4 in Bibliography, Appendix 1), rough set researchers have made further progress in inventing methods aimed, among others, at knowledge discovery and data mining, spatial reasoning, data reduction, concurrent system analysi

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A Rough Set Perspective on Knowledge Discovery in Information Systems: An Essay on the Topic of the e of data and knowledge analysis, due to a systematic growth of interest in this theory in the scientific community, witnessed by — among others — a bibliography of over four hundred research papers on rough sets and their applications produced in the last couple of years and appendiced to this coll

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Rough Mereology in Information Systems. A Case Study: Qualitative Spatial Reasoningof a . which gives for any two entities of discourse the degree in which one of them is a part of the other. Rough Mereology may be regarded as an extension of Rough Set Theory as it proposes to argue in terms of similarity relations induced from a rough inclusion instead of reasoning in terms of in

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