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Titlebook: Rough Sets and Knowledge Technology; 7th International Co Tianrui Li,Hung Son Nguyen,Hong Yu Conference proceedings 2012 Springer-Verlag Be

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發(fā)表于 2025-3-21 19:41:48 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Rough Sets and Knowledge Technology
副標(biāo)題7th International Co
編輯Tianrui Li,Hung Son Nguyen,Hong Yu
視頻videohttp://file.papertrans.cn/832/831922/831922.mp4
概述Up-to-date results.Fast track conference proceedings.State-of-the-art report
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Rough Sets and Knowledge Technology; 7th International Co Tianrui Li,Hung Son Nguyen,Hong Yu Conference proceedings 2012 Springer-Verlag Be
描述This book constitutes the refereed proceedings of the 7th International Conference on Rough Sets and Knowledge Technology, RSKT 2012, held in Chengdu, China during August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 63 revised papers (including 42 regular and 21 short papers) were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on rough sets and its generalizations, rough sets in data and knowledge processing, knowledge technology, advances in granular computing (AGC 2012 workshop), decision-theoretic rough set model and applications (special session), intelligent decision making and granular computing (special session), rough set foundations (special session).
出版日期Conference proceedings 2012
關(guān)鍵詞algorithms; data mining; decision trees; knowledge discovery; machine learning
版次1
doihttps://doi.org/10.1007/978-3-642-31900-6
isbn_softcover978-3-642-31899-3
isbn_ebook978-3-642-31900-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2012
The information of publication is updating

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發(fā)表于 2025-3-21 21:40:21 | 只看該作者
A New Intuitionistic Fuzzy Rough Set Approach for Decision Supportcalled believable rules, for better performance in decision-making. We provide an example to demonstrate the effectiveness of the proposed approach in multicriteria sorting and also a comparison with existing representative DRSA models.
板凳
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地板
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發(fā)表于 2025-3-22 09:36:41 | 只看該作者
Evidential Clustering or Rough Clustering: The Choice Is Yourslar K-means algorithm namely Rough k-means (RKM) is proposed and experimented with various datasets..In this paper we analyzed both the algorithms using synthetic, real and standard datasets to determine similarities of these two clustering approaches and focused on the strengths of each approach.
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發(fā)表于 2025-3-22 15:57:47 | 只看該作者
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發(fā)表于 2025-3-22 19:14:51 | 只看該作者
A Fuzzy-Rough Sets Based Compact Rule Induction Method for Classifying Hybrid Datae-art methods for hybrid data learning. Comparative studies indicate that rule sets extracted by this method can not only achieve comparable accuracy, but also get more compact rule sets. It is therefore concluded that the proposed method is effective for hybrid data learning.
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發(fā)表于 2025-3-22 22:33:37 | 只看該作者
Conference proceedings 2012 China during August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 63 revised papers (including 42 regular and 21 short papers) were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on rough sets
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發(fā)表于 2025-3-23 03:59:31 | 只看該作者
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發(fā)表于 2025-3-23 07:40:50 | 只看該作者
Data-Driven Valued Tolerance Relationl calculation method of tolerance degree needs to know the probability distribution of an information system in advance, and it is also difficult to select a suitable threshold. In this paper, a data-driven valued tolerance relation is proposed based on the idea of data-driven data mining. The new c
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