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Titlebook: A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications; Dmitri A. Viattchenin Book 2013 Springer-Verlag Berlin Heid

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發(fā)表于 2025-3-21 17:35:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications
影響因子2023Dmitri A. Viattchenin
視頻videohttp://file.papertrans.cn/142/141063/141063.mp4
發(fā)行地址Offers an interesting and original perspective on possibilistic clustering and uncertain data processing.Features a well-balanced material and a down-to-the earth exposition.Represents an important co
學(xué)科分類(lèi)Studies in Fuzziness and Soft Computing
圖書(shū)封面Titlebook: A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications;  Dmitri A. Viattchenin Book 2013 Springer-Verlag Berlin Heid
影響因子.The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects. ??The proposed approach can be used for solving different classification problems. Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing. Moreover,? a technique for constructing a subset of the most appropriate alternatives for a set of weak fuzzy preference relations, which are defined on a universe of alternatives, is described in detail, and a method for rapidly prototyping the Mamdani’s fuzzy inference systems is introduced. This book addresses engineers, scientists, professors, students and post-graduate students, who are interested in and work with fuzzy clustering and its applications.
Pindex Book 2013
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Back Matterapproaches to provide deeper mathematical insights.Explains .This book analyses and discusses bonds and bond portfolios. Different yields and duration measures are investigated for negative and positive interest rates. The transition from a single bond to a bond portfolio leads to the equation for t
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Dmitri A. ViattcheninOffers an interesting and original perspective on possibilistic clustering and uncertain data processing.Features a well-balanced material and a down-to-the earth exposition.Represents an important co
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Studies in Fuzziness and Soft Computinghttp://image.papertrans.cn/a/image/141063.jpg
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Zheng Xiao,Yang Guo,Gang Liu,Jiayi Du partitioning of a set of objects into subsets, called ., so that the objects belonging to the same cluster aare as similar as possible, and on the other hand, the objects belonging to different clusters are as dissimilar as possible. The resulting data partitioning improves data understanding and r
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Zheng Xiao,Yang Guo,Gang Liu,Jiayi Du of objects can be described by some fuzzy tolerance relation. A fuzzy cluster can be understood as some fuzzy subset implied by a fuzzy tolerance relation stipulating that a similarity degree of the elements of the fuzzy subset is not less than some threshold value. The condition stated above is a
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Marcel K?ster,Julian Gro?,Antonio Krüger objects for semi-supervised fuzzy clustering algorithms, feature selection, classification of the asymmetric data, fuzzy classifier prototyping, decision making, etc. The proposed approach to possibilistic clustering shows a close relationship to some of the problems mentioned above.
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