C4.5
eBook - PDF

C4.5

Programs for Machine Learning

  1. 302 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

C4.5

Programs for Machine Learning

Book details
Table of contents
Citations

About This Book

Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use, the source code (about 8, 800 lines), and implementation notes.

C4.5 starts with large sets of cases belonging to known classes. The cases, described by any mixture of nominal and numeric properties, are scrutinized for patterns that allow the classes to be reliably discriminated. These patterns are then expressed as models, in the form of decision trees or sets of if-then rules, that can be used to classify new cases, with emphasis on making the models understandable as well as accurate. The system has been applied successfully to tasks involving tens of thousands of cases described by hundreds of properties. The book starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting. Advantages and disadvantages of the C4.5 approach are discussed and illustrated with several case studies.

This book should be of interest to developers of classification-based intelligent systems and to students in machine learning and expert systems courses.

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Table of contents

  1. Front Cover
  2. C4.5: Programs for Machine Learning
  3. Copyright Page
  4. Table of Contents
  5. Preface
  6. Obtaining the C4.5 Code
  7. CHAPTER 1. Introduction
  8. CHAPTER 2. Constructing Decision Trees
  9. CHAPTER 3. Unknown Attribute Values
  10. CHAPTER 4. Pruning Decision Trees
  11. CHAPTER 5. From Trees to Rules
  12. CHAPTER 6. Windowing
  13. CHAPTER 7. Grouping Attribute Values
  14. CHAPTER 8. Interacting with Classification Models
  15. CHAPTER 9. Guide to Using the System
  16. CHAPTER 10. Limitations
  17. CHAPTER 11. Desirable Additions
  18. Appendix: Program Listings
  19. Author Index
  20. Subject Index