Data mining : practical machine learning tools and techniques /
Material type: TextPublisher: Amsterdam, Netherlands : Morgan Kaufmann Publishers, Elsevier, [2017]Copyright date: ©2017Edition: Fourth EditionDescription: xxxii, 621 pages : illustrations ; 24 cmContent type:- text
- unmediated
- volume
- 9780128042915
- 006.312 WID 23
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Book Non-borrowing | Library D | Information Technology | 006.312 WID (Browse shelf(Opens below)) | Not For Loan | 1004638 | |||
Book | Library D | Information Technology | 006.312 WID (Browse shelf(Opens below)) | Available | 1004639 |
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Includes bibliographical references and index.
Part I: Introduction to data mining -- Chapter 1. What’s it all about? -- Chapter 2. Input: Concepts, instances, attributes -- Chapter 3. Output: Knowledge representation -- Chapter 4. Algorithms: The basic methods -- Chapter 5. Credibility: Evaluating what’s been learned -- Part II. More advanced machine learning schemes -- Chapter 6. Trees and rules -- Chapter 7. Extending instance-based and linear models -- Chapter 8. Data transformations -- Chapter 9. Probabilistic methods -- Chapter 10. Deep learning -- Chapter 11. Beyond supervised and unsupervised learning -- Chapter 12. Ensemble learning -- Chapter 13. Moving on: applications and beyond -- References -- Index.
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