Please use this identifier to cite or link to this item:
https://lib.hpu.edu.vn/handle/123456789/33686
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kuhn, Max | en_US |
dc.contributor.author | Johnson, Kjell | en_US |
dc.date.accessioned | 2020-08-05T07:12:37Z | - |
dc.date.available | 2020-08-05T07:12:37Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.isbn | 978-1-4614-6848-6 | en_US |
dc.identifier.isbn | 978-1-4614-6849-3 | en_US |
dc.identifier.other | HPU2164638 | en_US |
dc.identifier.uri | https://lib.hpu.edu.vn/handle/123456789/33686 | - |
dc.description.abstract | 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. | en_US |
dc.format.extent | 595p. | en_US |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.subject | Model | en_US |
dc.subject | Non-Linear | en_US |
dc.subject | Predictive Models | en_US |
dc.subject | Regression Models | en_US |
dc.subject | Regression Trees | en_US |
dc.title | Applied Predictive Modeling | en_US |
dc.type | Book | en_US |
dc.size | 7,91 MB | en_US |
dc.department | Technology | en_US |
Appears in Collections: | Technology |
Files in This Item:
File | Description | Size | Format | |
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Applied-Predictive-Modeling.pdf Restricted Access | 8.11 MB | Adobe PDF | ![]() View/Open Request a copy |
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