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...
সংরক্ষণ করুন:
| প্রধান লেখক: | , |
|---|---|
| বিন্যাস: | Livre numérique |
| ভাষা: | Anglais |
| প্রকাশিত: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| সংস্করন: | 1st ed. 2013. |
| অনলাইন ব্যবহার করুন: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| টীকা: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| 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 |
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| 082 | |a 519.5 | ||
| 100 | 1 | |a Kuhn, Max. | |
| 245 | 1 | 0 | |a Applied Predictive Modeling |c by Max Kuhn, Kjell Johnson. |
| 250 | |a 1st ed. 2013. | ||
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a General Strategies Regression Models Classification Models Other Considerations Appendix References Indices | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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 | ||
| 700 | 1 | |a Johnson, Kjell. |4 aut | |
| 776 | 0 | |0 181556634 |t Applied predictive modeling |f Max Kuhn, Kjell Johnson |e [Édition corrigée au 5e tirage en 2016] |d 2013 |c New York |n Springer |p 1 vol. (XIII-600 p.) |z 978-1-461-46848-6 | |
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| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-CT9SW0P8-Q |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:747834415 |u https://ezproxy.univ-orleans.fr/login?url=https://dx.doi.org/10.1007/978-1-4614-6849-3 |z Accès Université d'Orléans | |
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