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Foundations of predictive analytics /
"This text is a summary of techniques of data analysis and modeling that the authors have encountered and used in our two-decades experience of practicing the art of applied data mining across many different fields. The authors have worked in this field together and separately in many large and...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press,
©2012.
|
| Colección: | Chapman & Hall/CRC data mining and knowledge discovery series.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Wu, James, |d 1965- | |
| 245 | 1 | 0 | |a Foundations of predictive analytics / |c James Wu, Stephen Coggeshall. |
| 260 | |a Boca Raton, FL : |b CRC Press, |c ©2012. | ||
| 300 | |a 1 online resource (xix, 317 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Chapman & Hall/CRC data mining and knowledge discovery series | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 1. Introduction -- 2. Properties of statistical distributions -- 3. Important matrix relationships -- 4. Linear modeling and regression -- 5. Nonlinear modeling -- 6. Time series analysis -- 7. Data preparation and variable selection -- 8. Model goodness measures -- 9. Optimization methods -- 10. Miscellaneous topics. | |
| 520 | |a "This text is a summary of techniques of data analysis and modeling that the authors have encountered and used in our two-decades experience of practicing the art of applied data mining across many different fields. The authors have worked in this field together and separately in many large and small companies, including the Los Alamos National Laboratory, Bank One (JPMorgan Chase), Morgan Stanley, and the startups of the Center for Adaptive Systems Applications (CASA), the Los Alamos Computational Group and ID Analytics. We have applied these techniques to traditional and nontraditional problems in a wide range of areas including consumer behavior modeling (credit, fraud, marketing), consumer products, stock forecasting, fund analysis, asset allocation, and equity and xed income options pricing. This monograph provides the necessary information for understanding the common techniques for exploratory data analysis and modeling. It also explains the details of the algorithms behind these techniques, including underlying assumptions and mathematical formulations. It is the authors' opinion that in order to apply di erent techniques to di erent problems appropriately, it is essential to understand the assumptions and theory behind each technique. It is recognized that this work is far from a complete treatise on the subject. Many excellent additional texts exist on the popular subjects and it was not a goal for this present text to be a complete compilation. Rather this text contains various discussions on many practical subjects that are frequently missing from other texts, as well as details on some subjects that are not often or easily found. Thus this text makes an excellent supplemental and referential resource for the practitioners of these subjects"-- |c Provided by publisher. | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Predictive control |x Mathematical models. | |
| 650 | 0 | |a Automatic control. | |
| 650 | 0 | |a Forecasting. | |
| 650 | 0 | |a Mathematical models. | |
| 650 | 0 | |a Computer science. | |
| 650 | 0 | |a Electronic data processing. | |
| 650 | 2 | |a Data Mining | |
| 650 | 2 | |a Forecasting | |
| 650 | 2 | |a Models, Theoretical | |
| 650 | 2 | |a Electronic Data Processing | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Commande prédictive |x Modèles mathématiques. | |
| 650 | 6 | |a Commande automatique. | |
| 650 | 6 | |a Prévision. | |
| 650 | 6 | |a Modèles mathématiques. | |
| 650 | 6 | |a Informatique. | |
| 650 | 7 | |a mathematical models. |2 aat | |
| 650 | 7 | |a computer science. |2 aat | |
| 650 | 7 | |a data processing. |2 aat | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Statistics. |2 bisacsh | |
| 650 | 7 | |a COMPUTERS |x Database Management |x Data Mining. |2 bisacsh | |
| 650 | 7 | |a COMPUTERS |x Machine Theory. |2 bisacsh | |
| 650 | 7 | |a Mathematical models |2 fast | |
| 650 | 7 | |a Forecasting |2 fast | |
| 650 | 7 | |a Electronic data processing |2 fast | |
| 650 | 7 | |a Computer science |2 fast | |
| 650 | 7 | |a Automatic control |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Predictive control |x Mathematical models |2 fast | |
| 700 | 1 | |a Coggeshall, Stephen. | |
| 758 | |i has work: |a Foundations of predictive analytics (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGC8BRdBrKRMgqrKjBPc8y |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Wu, James, 1965- |t Foundations of predictive analytics. |d Boca Raton, FL : CRC Press, ©2012 |z 9781439869468 |w (DLC) 2011049779 |w (OCoLC)690089872 |
| 830 | 0 | |a Chapman & Hall/CRC data mining and knowledge discovery series. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=870690 |z Texto completo |
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