Data mining : practical machine learning tools and techniques /

by Witten, Ian H
Additional authors: Frank, Eibe | Hall, Mark A
Series: [Morgan Kaufmann series in data management systems] Edition statement:3. ed. Published by : Morgan Kaufmann (Burlington, MA) Physical details: xxxiii, 629 p. ill. 24 cm ISBN:9780123748560 (pbk.). Year: 2011
    Average rating: 0.0 (0 votes)
Item type Current library Call number Status Date due Barcode
Book (Same day loan) Gräsvik
Referens
006.3 Available 080041486716
Book (loan) Gräsvik
006.3 Available 080041486715

Includes bibliographical references and index

PART I: Machine Learning Tools and Techniques. Ch 1. What's It All About? Ch 2. Input: Concepts, Instances, Attributes. Ch 3. Output: Knowledge Representation. Ch 4. Algorithms: The Basic Methods. Ch 5. Credibility: Evaluating What's Been Learned. PART II: Advanced Data Mining.Ch 6. Implementations: Real Machine Learning Schemes. Ch 7. Data Transformation. Ch 8. Ensemble Learning. Ch 9. Moving On: Applications and Beyond. PART III: The Weka Data MiningWorkbench. Ch 10. Introduction to Weka. Ch 11. The Explorer. Ch 12. The Knowledge Flow Interface. Ch 13. The Experimenter. Ch 14 The Command-Line Interface. Ch 15. Embedded Machine Learning. Ch 16. Writing New Learning Schemes. Ch 17. Tutorial Exercises for the Weka Explorer

Adress: Biblioteket, Blekinge Tekniska Högskola, 371 79 Karlskrona
Telefon: 0455 - 38 51 01
E-post: biblioteket@bth.se
Ansvarig för sidan: Biblioteket