Data mining |
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Cadre didactice indrumatoare |
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Obiective |
Cursul urmareste prezentarea notiunilor si metodelor de baza utilizate intr-o analiza a colectiilor mari de date pentru descoperirea de eventuale asocieri, sabloane, clasificari.
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Continut |
Vizualizarea si explorarea colectiilor de date
Reguli de asociere (reguli cantitative, reguli de corelare) Operatiile pe multimi de date. Algoritmi de optimizare a regasirilor din colectii mari de date OLAP. Interogari multidimensionale, dimensiuni, masuri, hipercuburi Modele abstracte de date pentru OLAP Clasificare si grupare Similaritati matematice |
Bibliografie |
1. David Hand, Heikki Mannila, Padhraic Smyth, Principles of Data Mining, MIT Press 2001.
2. Olivia Parr Rud, Data Mining Cookbook. Modeling Data for Marketing, Risk, and Customer Relationship Management, John Wiley & Sons 2001. 3. Humphries Hawkins Dy, Data Warehousing Architecture and Implementation, Prentice Hall PTR 1998. 4. Tom Soukup and Ian Davidson, Visual Data Mining: Techniques and Tools for Data Visualization and Mining, Wiley & Sons 2003. 5. Kimball, R. and M. Ross, The Data Warehouse Tool Kit, Second Edition. New York: John Wiley & Sons 2002. |
Evaluare |