Applied Predictive Modeling

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications...

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書誌詳細
主要な著者: Kuhn, Max, Johnson, Kjell (著者)
フォーマット: Livre numérique
言語:Anglais
出版事項: New York, NY : Springer New York [20..].
Cham : Springer Nature
版:1st ed. 2013.
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Edition sous un autre format:• Applied predictive modeling, Max Kuhn, Kjell Johnson, [Édition corrigée au 5e tirage en 2016], 2013, New York, Springer, 1 vol. (XIII-600 p.), 978-1-461-46848-6
その他の書誌記述
要約:This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages.  Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development.  He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D.  His scholarly work centers on the application and development of statistical methodology and learning algorithms
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ISBN:9781461468493
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