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Data mining : practical machine learning tools and techniques /

By: Contributor(s): Material type: TextTextPublisher: Amsterdam, Netherlands : Morgan Kaufmann Publishers, Elsevier, [2017]Copyright date: ©2017Edition: Fourth EditionDescription: xxxii, 621 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780128042915
Subject(s): DDC classification:
  • 006.312 WID 23
Contents:
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Book Non-borrowing Book Non-borrowing Library D Information Technology 006.312 WID (Browse shelf(Opens below)) Not For Loan 1004638
Book Book Library D Information Technology 006.312 WID (Browse shelf(Opens below)) Available 1004639
Total holds: 0

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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