Titlebook: Rough Sets and Current Trends in Computing; First International Lech Polkowski,Andrzej Skowron Conference proceedings 1998 Springer-Verlag

Credence

0302-9743 98, held in Warsaw, Poland, in June 1998..The volume presents 82 revised papers carefully selected for inclusion in the proceedings; also included are five invited contributions. The volume is divided in topical sections on rough set methods, statistical inference, grammar systems and molecular comp

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Rough Sets - What Are They About?ineers and philosophers as a basic tool to classify and utilize concepts in their respective domains of activity. We discuss the differences between rough sets and other approaches to incomplete and imprecise information such as fuzzy logic and logics that formalize the process of “jumping to conclusions”.

Diatribe

0302-9743 utations, logic in rough sets, intelligent control, rough sets in knowledge discovery and data discovery, data mining, evolutionary computation, hybrid methods, etc..978-3-540-64655-6978-3-540-69115-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

溫順

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Conference proceedings 1998n Warsaw, Poland, in June 1998..The volume presents 82 revised papers carefully selected for inclusion in the proceedings; also included are five invited contributions. The volume is divided in topical sections on rough set methods, statistical inference, grammar systems and molecular computations,

補助

Deviation and Association Patterns for Subgroup Mining in Temporal, Spatial, and Textual Data Basesf knowledge discovery in data bases (KDD). A mining step typically relies on strategies for systematic search in large hypotheses spaces guided by the autonomous evaluation of statistical tests. We describe the subgroup mining approach that is based on deviation and association patterns. A typical d

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座右銘

Reasoning about Data — A Rough Set Perspectivet is shown that decision rules can be interpreted as a generalization of the . inference rule, however there is an essential difference between these two concepts. Decision rules in the rough set approach are used to describe dependencies in data, whereas . is used in general to derive conclusions f

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Information Granulation and its Centrality in Human and Machine Intelligencemation granulation in human cognition, human reasoning and human decision-making. In many contexts, information granulation is a reflection of the finiteness of human ability to resolve detail and store information. In many other contexts, granulation is employed to solve a complex problem by partit