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Titlebook: Rankings and Preferences; New Results in Weigh Joaquim Pinto da Costa Book 2015 The Author(s) 2015 microarray data.principal component anal

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發(fā)表于 2025-3-21 20:07:27 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Rankings and Preferences
副標(biāo)題New Results in Weigh
編輯Joaquim Pinto da Costa
視頻videohttp://file.papertrans.cn/822/821146/821146.mp4
概述Numerous applications help the reader to learn quickly.Contains two special chapters on two very popular weighted correlation coefficients.Describes an easy way of using weighted correlation with alre
叢書名稱SpringerBriefs in Statistics
圖書封面Titlebook: Rankings and Preferences; New Results in Weigh Joaquim Pinto da Costa Book 2015 The Author(s) 2015 microarray data.principal component anal
描述.This book examines in detail the correlation, more precisely the weighted correlation and applications?involving rankings. A general application?is the evaluation of methods to predict rankings. Others involve?rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present?new?weighted?correlation coefficients and new methods of weighted principal component analysis..We also introduce new methods of dimension reduction and clustering for time series data and describe some theoretical results on the weighted correlation coefficients in separate sections..
出版日期Book 2015
關(guān)鍵詞microarray data; principal component analysis; ranking; time series; weighted correlation
版次1
doihttps://doi.org/10.1007/978-3-662-48344-2
isbn_softcover978-3-662-48343-5
isbn_ebook978-3-662-48344-2Series ISSN 2191-544X Series E-ISSN 2191-5458
issn_series 2191-544X
copyrightThe Author(s) 2015
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 20:41:52 | 只看該作者
板凳
發(fā)表于 2025-3-22 00:55:48 | 只看該作者
Book 2015f weighted principal component analysis..We also introduce new methods of dimension reduction and clustering for time series data and describe some theoretical results on the weighted correlation coefficients in separate sections..
地板
發(fā)表于 2025-3-22 05:22:33 | 只看該作者
2191-544X escribes an easy way of using weighted correlation with alre.This book examines in detail the correlation, more precisely the weighted correlation and applications?involving rankings. A general application?is the evaluation of methods to predict rankings. Others involve?rankings representing human p
5#
發(fā)表于 2025-3-22 11:09:49 | 只看該作者
Introduction,s, the comparisons of different rankings by means of an appropriate, weighted, correlation coefficient is used. Some weighted correlation coefficients will be presented and analyzed in the book. We will also present some interesting applications like for instance in bioinformatics, principal component analysis, and clustering.
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發(fā)表于 2025-3-22 16:14:34 | 只看該作者
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發(fā)表于 2025-3-22 18:38:28 | 只看該作者
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發(fā)表于 2025-3-22 23:37:10 | 只看該作者
Introduction,f data analysis tools, stock trading support, information retrieval, meta-learning and recommender systems. For the evaluation of the different methods, the comparisons of different rankings by means of an appropriate, weighted, correlation coefficient is used. Some weighted correlation coefficients
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發(fā)表于 2025-3-23 05:01:04 | 只看該作者
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