TY  - BOOK
AU  - Witten, Ian  H.
AU  - Frank, Eibe
AU  - Hall, Mark A.
AU  - Pal, Christopher J.
TI  - Data mining : practical machine learning tools and techniques
SN  - 9780128042915
U1  - 006.312 
PY  - 2017///
CY  - Cambridge
PB  -  MA : Morgan Kaufmann
KW  - Data mining
N1  -  	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
ER  -