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Seriation in Combinatorial and Statistical Data Analysis / by Israël César Lerman, Henri Leredde
(Advanced Information and Knowledge Processing. ISSN:21978441)

データ種別	電子ブック
版	1st ed. 2022.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2022
大きさ	XIV, 277 p. 114 illus., 6 illus. in color : online resource
著者標目	*Lerman, Israël César author Leredde, Henri author SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002438	Computer Scinece R0 2005-6,2022-3				9783030926946

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一般注記	Preface -- Acknowledgements -- General Introduction. Methods and History -- Seriation from Proximity Variance Analysis -- Main Approachs in Seriation. The Attraction Pole Case -- Comparing Geometrical and Ordinal Seriation Methods in Formal and Real Cases -- A New Family of Combinatorial Algorithms in Seriation -- Clustering Methods from Proximity Variance Analysis -- Conclusion and Developments This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering. Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods: Geometric representation methods Algorithmic and Combinatorial methods Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields HTTP:URL=https://doi.org/10.1007/978-3-030-92694-6
件　名	LCSH:Data mining LCSH:Computer science -- Mathematics 全ての件名で検索 LCSH:Machine learning FREE:Data Mining and Knowledge Discovery FREE:Mathematics of Computing FREE:Machine Learning
分　類	LCC:QA76.9.D343 DC23:006.312
書誌ID	EB00001826
ISBN	9783030926946