Perspectives on data mining

International Journal of Market Research

Volumn 52, Issue 1, 2010, Pages

  Adams, Niall M ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 76349094934     PISSN: 14707853     EISSN: None     Source Type: Journal    
DOI: 10.2501/s147078531020103x     Document Type: Article

References (15)

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2. Agrawal, R., Imielinski, T. & Swami, A. (1993) Mining association rules between sets of items in large databases. Proceedings of the ACM SIGMOD Conference on Management of Data (SIGMOD '93), ACM Press, pp. 307-328.
3. Chiu, S. & Tavella, D. (2008) Data Mining and Market Intelligence for Optimal Marketing Returns, Burlington, MA: Butterworth-Heinemann.
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5. Hand, D.J. (1999) Statistics and data mining: intersecting disciplines. SIGKDD Explorations, 1, pp. 16-19. doi:10.1145/846170.846171
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7. Hand, D.J., Mannila, H. & Smyth, P. (2001) Principles of Data Mining. Cambridge, MA: MIT Press.
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9. Hastie, T., Tibshirani, R. & Friedman, J. (2001) The Elements of Statistical Learning. New York: Springer.
10. Mays, E. (2005) Handbook of Credit Scoring. Chicago, IL: Financial World Press.
11. R Development Core Team (2006) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (http://www.R-project.org).
12. Shearer, C. (2000) The CRISP-DM model: the new blueprint for data mining. Journal of Data Warehousing, 5, 4, pp. 13-22.
13. Wasserman, L. (2004) All of Statistics: A Concise Course in Statistical Inference. New York: Springer.
14. Weston, D.J., Hand, D.J., Adams, N.M., Whitrow, C. & Juszczak, P. (2008) Plastic card fraud detection using peer group analysis. Advances in Data Analysis and Classification, 2, 1, pp. 45-62. doi:10.1007/s11634-008-0021-8
15. Witten, I.H. & Frank, E. (2005) Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (2nd edn). San Francisco, CA: Morgan Kaufmann.