عنوان
پدید آورنده
موضوع
رده
QA 76.9 .D343 W58 2011
QA
76
.
9
.
D343
W58
2011
کتابخانه
محل استقرار
electronic
Witten, I. H. )Ian H.(
Data mining : practical machine learning tools and techniques
Burlington, MA
Morgan Kaufmann
2011
xxxiii, 629 p. : ill. ; 24 cm
]Morgan Kaufmann series in data management systems[
Includes bibliographical references )p. 587-605( and index
Ian H. Witten, Eibe Frank, Mark A. Hall
3rd ed
Part I. Machine Learning Tools and Techniques: 1. What's iIt all about?; 2. Input: concepts, instances, and attributes; 3. Output: knowledge representation; 4. Algorithms: the basic methods; 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: 6. Implementations: real machine learning schemes; 7. Data transformation; 8. Ensemble learning; 9. Moving on: applications and beyond -- Part III. The Weka Data MiningWorkbench: 01. Introduction to Weka; 11. The explorer -- 21. The knowledge flow interface; 31. The experimenter; 41 The command-line interface; 51. Embedded machine learning; 61. Writing new learning schemes; 71. Tutorial exercises for the weka explorer
، Data mining
QA
76
.
9
.
D343
W58
2011
AU
AU Frank, Eibe
AU Hall, Mark A
TI
SE
SE Morgan Kaufmann series in data management systems
