Data mining: practical machine learning tools and techniques
Ian H. Witten; Eibe Frank; Mark A. Hall (Elsevier , 2011)
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| 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: 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. |
| No. Panggil : | 006.312 WIT d |
| Entri utama-Nama orang : | |
| Entri tambahan-Nama orang : | |
| Subjek : | |
| Penerbitan : | Amsterdam: Elsevier , 2011 |
| Sumber Pengatalogan: | LibUI eng rda |
| ISBN: | 9780123748560 |
| Tipe Konten: | text |
| Tipe Media: | unmediated |
| Tipe Carrier: | volume |
| Edisi: | Third edition |
| Catatan Seri: | Morgan Kaufmann series in data management systems |
| Catatan Umum: | Includes bibliographical references and index |
| Catatan Versi Asli: | |
| Deskripsi Fisik: | xxxiii, 629 pages : illustration ; 24 cm |
| Lembaga Pemilik: | Universitas Indonesia |
| Lokasi: | Perpustakaan UI, Lantai 2 |
| No. Panggil | No. Barkod | Ketersediaan |
|---|---|---|
| 006.312 WIT d | 01-15-01784 | TERSEDIA |
| 006.312 WIT d | 01-15-01775 | TERSEDIA |
| Ulasan: |
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