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Titlebook: Data Science, Classification, and Related Methods; Proceedings of the F Chikio Hayashi,Keiji Yajima,Yasumasa Baba Conference proceedings 19

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書目名稱Data Science, Classification, and Related Methods
副標(biāo)題Proceedings of the F
編輯Chikio Hayashi,Keiji Yajima,Yasumasa Baba
視頻videohttp://file.papertrans.cn/264/263140/263140.mp4
概述Helps the reader to gather data and to use search tools for analyzing and interpreting large and complex data sets.Presents a wide field of applications of interest not only to data analysts, mathemat
叢書名稱Studies in Classification, Data Analysis, and Knowledge Organization
圖書封面Titlebook: Data Science, Classification, and Related Methods; Proceedings of the F Chikio Hayashi,Keiji Yajima,Yasumasa Baba Conference proceedings 19
描述This volume, Data Science, Classification, and Related Methods, contains a selection of papers presented at the Fifth Conference of the International Federation of Oassification Societies (IFCS-96), which was held in Kobe, Japan, from March 27 to 30,1996. The volume covers a wide range of topics and perspectives in the growing field of data science, including theoretical and methodological advances in domains relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge discovery and seeking. It gives a broad view of the state of the art and is intended for those in the scientific community who either develop new data analysis methods or gather data and use search tools for analyzing and interpreting large and complex data sets. Presenting a wide field of applications, this book is of interest not only to data analysts, mathematicians, and statisticians but also to scientists from many areas and disciplines concerned with complex data: medicine, biology, space science, geoscience, environmental science, infonnation science, image and pattern analysis, economics, statistics, social sciences, psychology, cognitive science, behavi
出版日期Conference proceedings 1998
關(guān)鍵詞calculus; classification; data analysis; decision making; multidimensional scaling; data structures
版次1
doihttps://doi.org/10.1007/978-4-431-65950-1
isbn_softcover978-4-431-70208-5
isbn_ebook978-4-431-65950-1Series ISSN 1431-8814 Series E-ISSN 2198-3321
issn_series 1431-8814
copyrightSpringer Japan 1998
The information of publication is updating

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Cluster Validationrrect conclusions, by validating the results of a cluster analysis. The paper provides an overview of recent work in this area of cluster validation. Material covered includes: the distinction between external, internal, and relative clustering indices; types of null model, including ‘data-influence
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Fitting Graphs and Trees with Multidimensional Scaling Methodsework for fitting a particular class of graphs, which includes additive trees, hierarchical trees and circumplex structures. It is shown how to parametrize this fitting problem in terms of a lattice of subsets, and how inclusion relations between feature sets lead to additivity of distance along pat
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Classification and data analysis in financeistorical context is given. It is shown that the emerging of modern finance was made possible due to use of quantitative methods. The presented applications are divided into two main groups: 1) analysis of financial investments and markets, 2) corporate finance. The review is put in the framework wh
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Some Trends in the Classification of Variableshe integral transformation by the (probabilistic) distribution function of some suitable sample statistics. Some properties of those methods we have studied are remembered and/or derived here. Applications on either simulated or real data set have shown this approach performs better than the traditi
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