TY  - BOOK
AU  - Witten Ian H.[et al.]
TI  - Data Mining : Practical Machine Learning tools and techniques
SN  - 9780128042915
AV  - HD30.2 .D38 2017
PY  - 2017///
CY  - Amsterdam
PB  -   Morgan Kaufmann
N1  - Previous 3rd edition:2011; Part I: Introduction to data mining 1. What’s it all about? 2. Input: Concepts, instances, attributes 3. Output: Knowledge representation 4. Algorithms: The basic methods 5. Credibility: Evaluating what’s been learned Part II. More advanced machine learning schemes 6. Trees and rules 7. Extending instance-based and linear models 8. Data transformations 9. Probabilistic methods 10. Deep learning 11. Beyond supervised and unsupervised learning 12. Ensemble learning 13. Moving on: applications and beyond
N2  - This work offers a grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations
ER  -