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Titlebook: Grade Models and Methods for Data Analysis; With Applications fo Teresa Kowalczyk,El?bieta Pleszczyńska,Frederick R Book 2004 Springer-Verl

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書目名稱Grade Models and Methods for Data Analysis
副標(biāo)題With Applications fo
編輯Teresa Kowalczyk,El?bieta Pleszczyńska,Frederick R
視頻videohttp://file.papertrans.cn/388/387730/387730.mp4
概述Provides a new grade methodology for intelligent data analysis.The only book presently available covering both the theory and application of grade data analysis.Includes supplementary material:
叢書名稱Studies in Fuzziness and Soft Computing
圖書封面Titlebook: Grade Models and Methods for Data Analysis; With Applications fo Teresa Kowalczyk,El?bieta Pleszczyńska,Frederick R Book 2004 Springer-Verl
描述.This book provides a new grade methodology for intelligent data analysis. It introduces a specific infrastructure of concepts needed to describe data analysis models and methods. This monograph is the only book presently available covering both the theory and application of grade data analysis and therefore aiming both at researchers, students, as well as applied practitioners. The text is richly illustrated through examples and case studies and includes a short introduction to software implementing grade methods, which can be downloaded from the editors..
出版日期Book 2004
關(guān)鍵詞Analysis of Populations of Data; Categorization of Data; Cluster Analysis; Concentration; Concentration
版次1
doihttps://doi.org/10.1007/978-3-540-39928-5
isbn_softcover978-3-642-53561-1
isbn_ebook978-3-540-39928-5Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer-Verlag Berlin Heidelberg 2004
The information of publication is updating

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Univariate Lilliputian Model II, earnings . to female earnings . happened to be convex. This indicated a clear monotone trend: the higher the earnings macrocategory, the stronger the domination of male earnings over female earnings. Departures from convexity were noted for less aggregated data earnings.
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Preliminary concepts of bivariate dependence,meters based on concentration measures (applied e.g., to pairs of conditional distributions). In this way concepts belonging to the Univariate Lilliputian Model (???) supplement and help one to visualize the traditional model of bivariate dependence.
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Book 2004therefore aiming both at researchers, students, as well as applied practitioners. The text is richly illustrated through examples and case studies and includes a short introduction to software implementing grade methods, which can be downloaded from the editors..
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C. Cheniclet,C. Bernard-Dagan,G. Pauly local maxima starting from the original table after the random permutations of its rows and columns, and then selects the highest value of .* as the global maximum (or at least a very good approximation of the global maximum).
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