A Comparison of Approaches For Maximizing Business Payoff of Prediction Models

Proceedings - 2nd International Conference on Knowledge Discovery and Data Mining, KDD 1996

Volumn , Issue , 1996, Pages 195-201

  Brij, Masand ^a   Gregory, Piatetsky Shapiro ^a  

^a VERIZON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

BEHAVIOR-BASED; CUSTOMER BEHAVIOR; CUSTOMER VALUES; DATABASE MARKETING; MARKETING APPLICATION; OPTIMISATIONS; PREDICTION MODELLING; TEST SETS; TRAINING PROCESS; TRAINING SETS;

SALES;

EID: 85173796479     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

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2. Dasarathy, B.V. 1991. Nearest Neighbor Norms: NN Pattern Clas¬sification techniques, Los Alamitos, CA: IEEE Press.
3. Fayyad,U, Platetsky-Shapiro, G. P. Smyth, and Uthurusamy, R. 1996. Advances in Knowledge Discovery and Data Mining, Cam¬bridge, MA; AAAI/MIT Press.
4. Kohavi, R. and Sommerfield, IX 1995. Feature Subset Selection Using fire Wrapper Method: Overfittlng and Dynamic Search Space Topology. In Proceedings of KDD-95: First International Conference on Knowledge Discovery and Data Mining, 192-197. Menlo Park, CA: AAAI Press.
5. Platetsky-Shapito, G, and Frawley, W. 1991. Knowledge Discov¬ery in Databasesi Cambridge, MA: AAAI/MIT Press.
6. Rumelhart, D. E., Hinton, G, E & Williams, R J. 1986, Learning internal representations by error propagation. In Parallel Distrib¬uted Processing: Explorations in the microstructure of cognition. Volume I: Foundations. Cambridge, MA: MIT Press/Bradford Books, pp 318 -362.
7. Quinlan, J. R. 1993. C4.5: Programs for Machine Learning. Los Gates, CA: Morgan Kauffman.