Data mining : practical machine learning tools and techniques /
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaime...
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| Otros Autores: | , , |
| Formato: | Libro |
| Lenguaje: | Inglés |
| Publicado: |
Cambridge, MA, United States :
Morgan Kaufmann,
2017.
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| Edición: | 4a.ed. |
| Materias: | |
| Acceso en línea: | Ingresa con la contraseña de EBSCO |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 03175nam a22002537a 4500 | ||
|---|---|---|---|
| 008 | 250225b ||||| |||| 00| 0 eng d | ||
| 020 | |a 9780128043578 | ||
| 040 | |a AR-FvUNAJ | ||
| 041 | |a eng | ||
| 100 | 1 | |9 21236 |a Witten, Ian H. | |
| 245 | 1 | 0 | |a Data mining : |b practical machine learning tools and techniques / |c Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal |
| 250 | |a 4a.ed. | ||
| 260 | |a Cambridge, MA, United States : |b Morgan Kaufmann, |c 2017. | ||
| 300 | |a xxxii, 621 p. | ||
| 500 | |a Descargar, imprimir, guardar y enviar por correo electrónico hasta 40 páginas permitidas. Descarga completa del libro electrónico. Debe tener instalado Adobe Digital Editions para leer el eBook. | ||
| 520 | |a Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the bookOnline Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the bookTable of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projectsPresents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methodsIncludes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interfaceIncludes open-access online courses that introduce practical applications of the material in the book | ||
| 650 | 0 | |9 9478 |a MINERIA DE DATOS | |
| 700 | 1 | |9 21244 |a Frank, Eibe | |
| 700 | 1 | |9 21245 |a Hall, Mark A. | |
| 700 | 1 | |9 21246 |a Pal, Christopher J. | |
| 856 | |z Ingresa con la contraseña de EBSCO |u https://research.ebsco.com/c/6n4nn2/search/details/kzzsvcay75?db=nlebk&limiters=None&q=Data%20mining | ||
| 942 | |2 ddc |c LIBRO DIGI | ||
| 980 | |6 2 |a Virginia Figueroa |8 2 |g Virginia Figueroa | ||
| 999 | |c 10742 |d 10742 | ||