Local cover image
Local cover image

Data mining : practical machine learning tools and techniques.

By: Contributor(s): Material type: TextOriginal language: English Publisher: United States : Morgan Kaufmann, 2017Edition: 4Description: 621 páginas : : figuras , tablesContent type:
  • texto
Media type:
  • sin mediación
Carrier type:
  • volumen
ISBN:
  • 9780128042915
Subject(s): DDC classification:
  • 23 006.312 W829d
Contents:
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. -- 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. -- 10.5 Stochastic Deep Networks. -- Chapter 11. Beyond supervised and unsupervised learning. -- Chapter 12. Ensemble learning. -- Chapter 13. Moving on: applications and beyond.
Summary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
LIBROS - MATERIAL GENERAL BIBLIOTECA CENTRAL General 006.312 W829d (Browse shelf(Opens below)) Ej.:1 Available 086922
Total holds: 0

Contents.

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. -- 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. -- 10.5 Stochastic Deep Networks. -- Chapter 11. Beyond supervised and unsupervised learning. -- Chapter 12. Ensemble learning. -- Chapter 13. Moving on: applications and beyond.

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.

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer

Local cover image