Machine learning

Author(s)

• Mitchell, Tom Michael

Bibliographic Information

Machine learning

Tom M. Mitchell

（McGraw-Hill computer science series, Artificial intelligence）

McGraw-Hill, c1997

Note

Includes bibliographical references and indexes

Description and Table of Contents

Description

This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.

Table of Contents

Chapter 1. IntroductionChapter 2. Concept Learning and the General-to-Specific OrderingChapter 3. Decision Tree LearningChapter 4. Artificial Neural NetworksChapter 5. Evaluating HypothesesChapter 6. Bayesian LearningChapter 7. Computational Learning TheoryChapter 8. Instance-Based LearningChapter 9. Inductive Logic ProgrammingChapter 10. Analytical LearningChapter 11. Combining Inductive and Analytical LearningChapter 12. Reinforcement Learning.

by "Nielsen BookData"

Details

• NCID: BA30444721
• ISBN:
  • 9780070428072
• LCCN: 97007692
• Country Code: us
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: New York
• Pages/Volumes: xvii, 414 p.
• Size: 25 cm
• Classification:
  • LCC : Q325.5
  • DC21 : 006.3/1
• Subject Headings:
  • LCSH : Machine learning
  • LCSH : Computer algorithms
• Parent Bibliography ID:
  • BA00039928