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Kernel Ridge Regression in Clinical Research

Erschienen am 13.09.2022, 1. Auflage 2022
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Bibliografische Daten
ISBN/EAN: 9783031107160
Sprache: Englisch
Umfang: xvii, 289 S., 1 s/w Illustr., 289 p. 1 illus. With
Einband: gebundenes Buch

Beschreibung

IBM (international business machines) has published in its SPSS statistical software 2022 update a very important novel regression method entitled Kernel Ridge Regression (KRR). It is an extension of the currently available regression methods, and is suitable for pattern recognition in high dimensional data, particularly, when alternative methods fail. Its theoretical advantages are plenty and include the

Produktsicherheitsverordnung

Hersteller:
Springer Verlag GmbH
juergen.hartmann@springer.com
Tiergartenstr. 17
DE 69121 Heidelberg

Autorenportrait

Professor Dr. T.J. Cleophas is internist / clinical pharmacologist / statistician at the educational Albert Schweitzer Hospital Dordrecht Netherlands. He is the writer of many statistics textbooks, and he tutors statistics at the Universities of Amsterdam, Rotterdam, Utrecht, Maastricht, Leiden, Nijmegen, Netherlands. In 2020-2022 he was the invited author and editor of Springer Heidelberg Series on Machine Learning and Statistics Applied to Clinical Studies, which were bought by over 30 million professionals involved in Coronavirus research. He is currently completing an edition entitled "Kernel Ridge Regression in Clinical Research", addressing a novel methodology for big and multidimensiomal data analysis. Professor Dr. A.H. Zwinderman is mathematical PhD, full professor of statistics, and principal investigator at the Academic Medical Center, University of Amsterdam. He authored 663 scientific papers and developed many novel statistical methods with particular focus on omics and big data research. He is co-founder of the sparse canonical methodology for the analysis of data with thousands of predictor variables, and together with Professor Cleophas he contributed to the statistical methods series in the journal Circulation. Much of his current work involves studies based on methodologies like parallel computing, the use of clustercomputers, GPU computing, and grid computing.