| 书目名称 | Data Mining, Rough Sets and Granular Computing | | 编辑 | Tsau Young Lin,Yiyu Y. Yao,Lotfi A. Zadeh | | 视频video | | | 概述 | The book integrates data mining, rough sets and granular computing.Includes supplementary material: | | 丛书名称 | Studies in Fuzziness and Soft Computing | | 图书封面 |  | | 描述 | During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing. | | 出版日期 | Book 2002 | | 关键词 | Extension; Scoring; approximation; calculus; classification; data analysis; data mining; fuzzy sets; knowled | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-7908-1791-1 | | isbn_softcover | 978-3-7908-2508-4 | | isbn_ebook | 978-3-7908-1791-1Series ISSN 1434-9922 Series E-ISSN 1860-0808 | | issn_series | 1434-9922 | | copyright | Springer-Verlag Berlin Heidelberg 2002 |
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发表于 2025-3-21 18:31:22
