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Titlebook: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing; 14th International C Davide Ciucci,Masahiro Inuiguchi,Guoyin Wang Conference p

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發(fā)表于 2025-3-21 17:56:27 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
副標題14th International C
編輯Davide Ciucci,Masahiro Inuiguchi,Guoyin Wang
視頻videohttp://file.papertrans.cn/832/831930/831930.mp4
概述Fast-track conference proceedings.State-of-the-art research.Up-to-date results
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing; 14th International C Davide Ciucci,Masahiro Inuiguchi,Guoyin Wang Conference p
描述.This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2013, held in Halifax, Canada in October 2013 as one of the co-located conference of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as inconsistency, incompleteness, non-determinism; fuzzy and rough hybridization; granular computing and covering-based rough sets; soft clustering; image and medical data analysis..
出版日期Conference proceedings 2013
關鍵詞approximation; big data; decision tables; machine learning; soft computing
版次1
doihttps://doi.org/10.1007/978-3-642-41218-9
isbn_softcover978-3-642-41217-2
isbn_ebook978-3-642-41218-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing978-3-642-41218-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Some New Progress in Analyzing and Mining Uncertain and Probabilistic Data for Big Data Analytics short article, we review some recent progress in mining uncertain and probabilistic data in the hope that the problems, progress, and challenges can inspire interdisciplinary dialogues and lead to new research opportunities.
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