The elements of statistical learning : data mining, inference, and prediction / Trevor Hastie, Robert Tibshirani, Jerome Friedman.
Material type:
TextLanguage: English Series: Springer series in statisticsPublisher: New York : Springer, 2017Edition: Second editionDescription: xxii, 745 páginas : ilustraciones, gráficos ; 24 cmContent type: texto Media type: sin mediación Carrier type: volumenISBN: 9780387848570 Subject(s): Estadística matemática -- Problemas, ejercicios, etc | Modelos matemáticos | Modelos lineales (Estadística) | Procesamiento automatizado de datos | Minería de datosDDC classification: 519.5 | Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|
Libros
|
Biblioteca CESA
Diagonal 34 A No. 5 A - 23 Casa Incolda PBX: 339 53 00 serviciosbiblioteca@cesa.edu.co |
General | 519.5 / H344e 2017 (Browse shelf(Opens below)) | Ej. 1 | Available | 7110001612 |
Browsing Biblioteca CESA shelves, Shelving location: Piso 1, Collection: General Close shelf browser (Hides shelf browser)
| 519.5 / H241p Pronósticos en los negocios / | 519.5 / H241p Pronósticos en los negocios / | 519.5 / H289i 1975 Introductory statistical analysis / | 519.5 / H344e 2017 The elements of statistical learning : data mining, inference, and prediction / | 519.5 / H465r R through excel : a spreadsheet interface for statistics, data analysis, and graphics / | 519.5 / H642e Estadística aplicada : a la administración y a la economía / | 519.5 / H793e Estadística básica para las ciencias sociales y del comportamiento / |
Incluye índice.
Incluye referencias bibliográficas.
1. Introducción, 2. Revisión de literatura, 3. Descripción de datos, 4. Metodología, 5. Resultados, 6. Conclusiones.
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics.
Click on an image to view it in the image viewer
There are no comments on this title.