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C4.5 : programs for machine learning /
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.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
San Mateo, Calif. :
Morgan Kaufmann Publishers,
�1993.
|
| Colección: | Morgan Kaufmann series in machine learning.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Quinlan, J. R. |q (John Ross), |d 1943- | |
| 245 | 1 | 0 | |a C4.5 : |b programs for machine learning / |c J. Ross Quinlan. |
| 260 | |a San Mateo, Calif. : |b Morgan Kaufmann Publishers, |c �1993. | ||
| 300 | |a 1 online resource (x, 302 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a The Morgan Kaufmann series in machine learning | |
| 504 | |a Includes bibliographical references (pages 291-296) and indexes. | ||
| 520 | |a 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. | ||
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2010. |5 MiAaHDL | ||
| 538 | |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |u http://purl.oclc.org/DLF/benchrepro0212 |5 MiAaHDL | ||
| 583 | 1 | |a digitized |c 2010 |h HathiTrust Digital Library |l committed to preserve |2 pda |5 MiAaHDL | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover; C4.5: Programs for Machine Learning; Copyright Page; Table of Contents; Preface; Obtaining the C4.5 Code; CHAPTER 1. Introduction; 1.1 Example: Labor negotiation settlements; 1.2 Other kinds of classification models; 1.3 What lies ahead; CHAPTER 2. Constructing Decision Trees; 2.1 Divide and conquer; 2.2 Evaluating tests; 2.3 Possible tests considered; 2.4 Tests on continuous attributes; CHAPTER 3. Unknown Attribute Values; 3.1 Adapting the previous algorithms; 3.2 Play/Don't Play example again; 3.3 Recapitulation; CHAPTER 4. Pruning Decision Trees; 4.1 When to simplify? | |
| 505 | 8 | |a 4.2 Error-based pruning4.3 Example: Democrats and Republicans; 4.4 Estimating error rates for trees; CHAPTER 5. From Trees to Rules; 5.1 Generalizing single rules; 5.2 Class rulesets; 5.3 Ranking classes and choosing a default; 5.4 Summary; CHAPTER 6. Windowing; 6.1 Example: Hypothyroid conditions revisited; 6.2 Why retain windowing?; 6.3 Example: The multiplexor; CHAPTER 7. Grouping Attribute Values; 7.1 Finding value groups by merging; 7.2 Example: Soybean diseases; 7.3 When to form groups?; 7.4 Example: The Monk's problems; 7.5 Uneasy reflections. | |
| 505 | 8 | |a CHAPTER 8. Interacting with Classification Models8.1 Decision tree models; 8.2 Production rule models; 8.3 Caveat; CHAPTER 9. Guide to Using the System; 9.1 Files; 9.2 Running the programs; 9.3 Conducting experiments; 9.4 Using options: A credit approval example; CHAPTER 10. Limitations; 10.1 Geometric interpretation; 10.2 Nonrectangular regions; 10.3 Poorly delineated regions; 10.4 Fragmented regions; 10.5 A more cheerful note; CHAPTER 11. Desirable Additions; 11.1 Continuous classes; 11.2 Ordered discrete attributes; 11.3 Structured attributes; 11.4 Structured induction. | |
| 505 | 8 | |a 11.5 Incremental induction11.6 Prospectus; Appendix: Program Listings; Brief descriptions of the contents of the files; Notes on some important data structures; File Makefile; Alphabetic index of routines; References and Bibliography; Author Index; Subject Index. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Algorithms. | |
| 650 | 0 | |a Computer programming. | |
| 650 | 0 | |a Computer algorithms. | |
| 650 | 2 | |a Algorithms |0 (DNLM)D000465 | |
| 650 | 2 | |a Machine Learning |0 (DNLM)D000069550 | |
| 650 | 6 | |a Apprentissage automatique. |0 (CaQQLa)201-0131435 | |
| 650 | 6 | |a Algorithmes. |0 (CaQQLa)201-0001230 | |
| 650 | 6 | |a Programmation (Informatique) |0 (CaQQLa)201-0002014 | |
| 650 | 7 | |a algorithms. |2 aat |0 (CStmoGRI)aat300065585 | |
| 650 | 7 | |a computer programming. |2 aat |0 (CStmoGRI)aat300054641 | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Computer algorithms |2 fast |0 (OCoLC)fst00872010 | |
| 650 | 7 | |a Algorithms |2 fast |0 (OCoLC)fst00805020 | |
| 650 | 7 | |a Computer programming |2 fast |0 (OCoLC)fst00872390 | |
| 650 | 7 | |a Machine learning |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 1 | 7 | |a Machine-learning. |2 gtt |
| 650 | 1 | 7 | |a Algoritmen. |2 gtt |
| 650 | 7 | |a Machine logique. |2 ram | |
| 650 | 7 | |a Apprentissage automatique. |2 ram | |
| 650 | 7 | |a Algorithmes. |2 ram | |
| 650 | 7 | |a Ordinateurs |x Programmation. |2 ram | |
| 776 | 0 | 8 | |i Print version: |a Quinlan, J.R. (John Ross), 1943- |t C4.5. |d San Mateo, Calif. : Morgan Kaufmann Publishers, �1993 |w (DLC) 92032653 |w (OCoLC)26547590 |
| 830 | 0 | |a Morgan Kaufmann series in machine learning. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780080500584 |z Texto completo |