| 000 | 01957cam a22003614a 4500 | ||
|---|---|---|---|
| 999 |
_c7003 _d7003 |
||
| 001 | 16490354 | ||
| 005 | 20190509094239.0 | ||
| 008 | 101005s2011 maua b 001 0 eng | ||
| 010 | _a 2010039827 | ||
| 020 | _a9780123748560 (pbk.) | ||
| 020 | _a0123748569 (pbk.) | ||
| 040 |
_aDLC _cDLC _dYDX _dBTCTA _dYDXCP _dBWX _dDEBSZ _dCDX _dIUL _dDLC _erda |
||
| 050 | 0 | 0 |
_aQA76.9.D343 _bW58 2011 |
| 082 | 0 | 0 |
_a006.312 _222 _bW.I.D |
| 100 | 1 |
_aWitten, I. H. _q(Ian H.) |
|
| 245 | 1 | 0 |
_aData mining : _bpractical machine learning tools and techniques / _cIan H. Witten, Eibe Frank, Mark A. Hall. |
| 250 | _a3rd ed. | ||
| 260 |
_aBurlington, MA : _bMorgan Kaufmann, _cc2011. |
||
| 300 |
_axxxiii, 629 p. : _bill. ; _c24 cm. |
||
| 336 |
_2rdacontent _atext |
||
| 337 |
_2rdamedia _aunmediated |
||
| 338 |
_2rdacarrier _avolume |
||
| 490 | 1 | _a[Morgan Kaufmann series in data management systems] | |
| 504 | _aIncludes bibliographical references (p. 587-605) and index. | ||
| 505 | 0 | _aPart 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: 10. Introduction to Weka; 11. The explorer -- 12. The knowledge flow interface; 13. The experimenter; 14 The command-line interface; 15. Embedded machine learning; 16. Writing new learning schemes; 17. Tutorial exercises for the weka explorer. | |
| 650 | 0 | _aData mining. | |
| 700 | 1 | _aFrank, Eibe. | |
| 700 | 1 | _aHall, Mark A. | |
| 830 | 0 | _aMorgan Kaufmann series in data management systems. | |
| 856 |
_3Abstract _uhttp://repository.fue.edu.eg/xmlui/handle/123456789/3458 |
||
| 942 |
_cBK _2ddc |
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