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Data mining for business intelligence : concepts, techniques, and applications in Microsoft Office Excel with XLMiner /
Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows read...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley,
©2010.
|
| Edición: | 2nd ed. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Shmueli, Galit, |d 1971- | |
| 245 | 1 | 0 | |a Data mining for business intelligence : |b concepts, techniques, and applications in Microsoft Office Excel with XLMiner / |c Galit Shmueli, Nitin R. Patel, Peter C. Bruce. |
| 250 | |a 2nd ed. | ||
| 260 | |a Hoboken, N.J. : |b Wiley, |c ©2010. | ||
| 300 | |a 1 online resource (xxiv, 404 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 | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Introduction -- Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating classification and predictive performance -- Multiple linear regression -- knearest neighbors (kNN) -- Naive bayes -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Association rules -- Cluster Analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Cases. | |
| 588 | 0 | |a Print version record. | |
| 520 | |a Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of DM techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples, now doubled in number in the second edit. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
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| 650 | 0 | |a Business |x Data processing. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Management |x Data processing. | |
| 650 | 6 | |a Gestion |x Informatique. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 7 | |a Business |x Data processing. |2 blmlsh | |
| 650 | 7 | |a Data mining. |2 blmlsh | |
| 650 | 7 | |a Management |x Data processing |2 fast | |
| 650 | 7 | |a Business |x Data processing |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 700 | 1 | |a Patel, Nitin R. |q (Nitin Ratilal) | |
| 700 | 1 | |a Bruce, Peter C., |d 1953- | |
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