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Titlebook: Clustering High--Dimensional Data; First International Francesco Masulli,Alfredo Petrosino,Stefano Rovett Conference proceedings 2015 Spri

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發(fā)表于 2025-3-21 18:59:27 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Clustering High--Dimensional Data
副標題First International
編輯Francesco Masulli,Alfredo Petrosino,Stefano Rovett
視頻videohttp://file.papertrans.cn/229/228547/228547.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Clustering High--Dimensional Data; First International  Francesco Masulli,Alfredo Petrosino,Stefano Rovett Conference proceedings 2015 Spri
描述.This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012. ..The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the general subject and issues of high-dimensional data clustering; present examples of techniques used to find and investigate clusters in high dimensionality; and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering.?.
出版日期Conference proceedings 2015
關(guān)鍵詞big data clustering; dimensionality reduction; high dimensional data analysis; machine learning; time se
版次1
doihttps://doi.org/10.1007/978-3-662-48577-4
isbn_softcover978-3-662-48576-7
isbn_ebook978-3-662-48577-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2015
The information of publication is updating

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What are Clusters in High Dimensions and are they Difficult to Find?,low-dimensional data set. Concentration of norm is one of the phenomena from which high-dimensional data sets can suffer. It means that in high dimensions – under certain general assumptions – the relative distances from any point to its closest and farthest neighbour tend to be almost identical. Si
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A Rough Fuzzy Perspective to Dimensionality Reduction,ny real–world problems. The focus of rough set theory is on the ambiguity caused by limited discernibility of objects in the domain of discourse; granules are formed as objects and are drawn together by the limited discernibility among them. On the other hand, membership functions of fuzzy sets enab
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