Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (vol. # 3641)
Publication year: 2005
ISBN: 978-3-540-31825-5
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The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signifcant results in many areas such as industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications.
Subject: Computer Science, artificial intelligence, cognition, data mining, evolution, evolutionary computation, fuzzy, information system, learning, machine learning, multimedia, probabilistic network, uncertain reasoning
