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Rank-based methods for shrinkage and selection : with application to machine learning / A. K. Md. Ehsanes Saleh, Mohammad Arashi, Resve A. Saleh, Mina Norouzirad

データ種別	電子ブック
出版者	(Hoboken, NJ : John Wiley & Sons, Inc)
出版年	2022
大きさ	1 online resource : illustrations (some color)
著者標目	*Saleh, A. K. Md. Ehsanes author Arashi, M 1981- author Saleh, Resve A. 1957- author Norouzirad, Mina author

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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	EB0005249	Wiley Online Library: Complete oBooks				9781119625438

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一般注記	Includes bibliographical references and index Introduction to rank-based regression -- Characteristics of rank-based penalty estimators -- Location and simple linear models -- Analysis of variance (ANOVA) -- Seemingly unrelated simple linear models -- Multiple linear regression models -- Partially linear multiple regression model -- Liu regression models -- Autoregressive models -- High-dimensional models -- Rank-based logistic regression -- Rank-based neural networks "The purpose of this book is to lay the groundwork for robust data science using rankbased methods. The field of machine learning has not yet fully embraced a class of robust estimators that would address issues that limit the value of least-squares estimation. For example, outliers in data sets may produce misleading results that are not suitable for inference. They can also affect results obtained from penalty estimators. We believe that robust estimators for regression problems are well-suited to data science. This book is intended to provide both practical and mathematical foundations in the study of rank-based methods. It will introduce a number of new ideas and approaches to the practice and theory of robust estimation and encourage readers to pursue further investigation in this field. While the main goal of this book is to provide a rigorous treatment of the subject matter, we begin with some introductory material to build insight and intuition about rank-based regression and penalty estimators, especially for those who are new to the topic and those looking to understand key concepts. To motivate the need for such methods, we will start with a discussion of the median as it is the key to rank-based methods and then build on that concept towards the notion of robust data science"-- Provided by publisher Description based on online resource; title from digital title page (viewed on April 06, 2022) John Wiley and Sons Wiley Online Library: Complete oBooks HTTP:URL=https://onlinelibrary.wiley.com/doi/book/10.1002/9781119625438
件　名	LCSH:Regression analysis LCSH:Big data LCSH:Machine learning MESH:Regression Analysis MESH:Machine Learning CSHF:Analyse de r�egression CSHF:Donn�ees volumineuses CSHF:Apprentissage automatique FREE:Big data FREE:Machine learning FREE:Regression analysis
分　類	LCC:QA278.2 DC23:519.5/36
書誌ID	EB00004538
ISBN	9781119625438