Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal.

Por:

Witten, I. H., (Ian H.) [autor]

Colaborador(es):

Tipo de material: Texto

texto

Tipo de medio:

sin medio

Tipo de soporte:

volumen

ISBN:

9780128042915

Tema(s):

Clasificación LoC:

QA 76 .9 .D343 W82 2017

Contenidos:

Part I: Introduction to data mining -- Chapter 1. What's it all about? -- Chapter 2. Input: Concepts, instances, attributes -- Chapter 3. Output: Knowledge representation -- Chapter 4. Algorithms: The basic methods -- Chapter 5. Credibility: Evaluating what's been learned -- Part II: More advanced machine learning schemes -- Chapter 6. Trees and rules -- Chapter 7. Extending instance-based and linear models -- Chapter 8. Data transformations -- Chapter 9. Probabilistic methods -- Chapter 10. Deep learning -- Chapter 11. Beyond supervised and unsupervised learning -- Chapter 12. Ensemble learning -- Chapter 13. Moving on: applications and beyond

Resumen: "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." -- P. web editorial

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Existencias
Tipo de ítem	Biblioteca actual	Biblioteca de origen	Colección	Signatura topográfica	Copia número	Estado	Notas	Fecha de vencimiento	Código de barras	Reserva de ítems
Libros para consulta en sala	Biblioteca Antonio Enriquez Savignac	Biblioteca Antonio Enriquez Savignac	COLECCIÓN RESERVA	QA 76 .9 .D343 W82 2017 (Navegar estantería(Abre debajo))	1	No para préstamo	Ingeniería en Datos e Inteligencia Organizacional		040445

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Incluye referencias bibliográficas: páginas 573-600

"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." -- P. web editorial

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Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal.