Applied Predictive Modeling - Grand Format

Edition en anglais

Max Kuhn

,

Kjell Johnson

Note moyenne 
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... Lire la suite
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Résumé

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.

Caractéristiques

  • Date de parution
    01/01/2016
  • Editeur
  • ISBN
    978-1-4614-6848-6
  • EAN
    9781461468486
  • Format
    Grand Format
  • Présentation
    Relié
  • Nb. de pages
    600 pages
  • Poids
    1.1 Kg
  • Dimensions
    16,2 cm × 24,2 cm × 3,8 cm

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À propos des auteurs

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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