01686nam a22002297a 4500001000400000003001100004008004100015020001800056040001300074080001600087100002300103245013100126250000800257260003800265300002100303336002700324337003300351338002800384505099600412650002301408700002501431653AR-FRRoUTN240828t2011    inu|||||r|||| 001 0 spa d  a9780470650936  aUTN FRRo0 a004.6220151 aLinoff, Gordon S. 10aData mining techniques :bfor marketing, sales, and customer relationship management /cGordon S. Linoff, Michael J. A. Berry.  a3rd  aIndianápolis : bWiley, c2011.  a847 p. ; c24 cm  2rdacontentatextobtxt  2rdamediaasin mediaciónbn  2rdacarrieravolumenbnc0 aIntroduction. -- Chapter 1. What id data mining and why do it?. -- Chapter 2. Data mining applications in marketing and customer relationship management. -- Chapter 3. The data minig process. -- Chapter 4. Statistics 101. -- Chapter 5. Descriptions and prediction. -- Chapter 6. Data mining using classic staristical techniques. -- Chapter 7. Decision trees. -- Chapter 8. Artificial neural networks. -- Chapter 9. Nearest neighbor approaches. -- Chapter 10. Knoeing whwn the worry. -- Chapter 11. Genetic algorithms and swarm intelligence. -- Chapter 12. ell me something new . -- Chapter 13. Finding islands of similarity. -- Chapter 14. Alternative approaches to cluster detections. -- Chapter 15. Market basket analysis ans associations rules. -- Chapter 16. Link analisys. -- Chapter 17. Data warehousing. -- Chapter 18. Buildind customer signatures. -- Chapter 19. Derived variables. -- Chapter 20. Too much of a good thing?. -- Chapter 21. Listen carefully to what your customers say.14aMINERÍA DE DATOS1 aBerry, Michael J. A.