Intelligent data analysis: Issues and opportunities

Intelligent Data Analysis

Volumn 2, Issue 2, 1998, Pages 67-79

  Hand, David J ^a  

^a OPEN UNIVERSITY   (United Kingdom)

Author keywords

Applications; Computers; Data types; Metadata; Models; Problems

Indexed keywords

COMPUTER TECHNOLOGY; DATA ANALYSTS; DATA TYPE; IMAGE DATA; INTELLIGENT DATA ANALYSIS; INTERACTIVE GRAPHICS; PROBLEMS; REAL TIME;

APPLICATIONS; COMPUTERS; METADATA; MODELS;

COMPUTER APPLICATIONS;

EID: 0003337418     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/IDA-1998-2202     Document Type: Article

References (21)

1. Bailey K.R., Generalizing the results of randomized clinical trials. Controlled Clinical Trials. 15, 15-23, 1994.
2. Boden M.A., Artificial Intelligence and Natural Man, Hassocks, Harvester Press, 1977.
3. Bradley c.E. and Smyth P., Applying classification algorithms in practice. Statistics and Computing. 7, 45-56, 1997.
4. Cowan C.D., Intercept studies, clinical trials, and cluster experiments: To whom can we extrapolate? Controlled Clinical Trials. 15,24-29, 1994.
5. Cox D.R. and Snell E.J., Applied Statistics: Principles and Examples, Chapman and Hall, London, 1981.
6. Darius P., Boucueau M., de Greef P., de Faber E., and Froeschl K., Modelling metadata. Statistical Journal of the United Nations-ECE. 10, 171-179,1993.
7. Diday E., Towards a Statistic of Metadata for Knowledge Analysis, in AI and Computer Power: The Impact on Statistics. (D.J. Hand, ed.) Chapman and Hall, London. 23-35, 1994.
8. Froeschl K.A., A metadata approach to statistical query processing. Statistics and Computing. 6, 11-29, 1996.
9. Gray J., Chaudhuri S., Boswortb A., Layman A., Reichart D., Venkatrao M., Pellow F., and Pirahesh H., Data cube: a relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Mining and Knowledge Discovery. 1,29-53, 1997.
10. Grove W.M. and Meehl P.E., Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: the clinical-statistical controversy. Psychology, Public Policy, and Law. 2, 293-323, 1996.
11. Hand D.J., Patterns in statistical strategy, in Artificial Intelligence and Statistics, (W.A. Gale, ed.) Addison-Wesley, Reading, Massachusetts, 355-387, 1984.
12. Hand D.J., Artificial Intelligence and Psychiatry, Cambridge University Press, Cambridge, 1985.
13. Hand D.J., Classification and Computers: Shifting the Focus, in COMPSTAT-Proceedings in Computational Statistics, 1996. ed. A. Prat. Physica-Verlag, 77-88, 1996.
14. Hand D.J., Statistics and the theory of measurement (with discussion). Journal of the Royal Statistical Society, Series A. 59,445-492,1996b.
15. Hand D.J., Construction and Assessment of Classification Rules, Wiley, Chichester, 1997.
16. Hand D.J. and Henley W.E., Statistical classification methods in consumer credit scoring: a review. Journal of the Royal Statistical Society, Series A. 160, 1997.
17. Hand D.J. and Jacka S., eds, Statistics in Finance, Edward Arnold, London, (Forthcoming), 1997.
18. Pregibon D., A DIY guide to statistical strategy, in Artificial Intelligence and Statistics, (W.A. Gale, ed), Addison-Wesley, Reading, Massachusetts, 389-399, 1984.
19. Rosenberg E. and Gleit A., Quantitative methods in credit management: A survey. Operations Research. 42, 589-613, 1994.
20. Thomas L.C., Crook J.N., and Edelman D.B. (eds), Credit Scoring and Credit Control. Clarendon Press, Oxford, 1992.
21. Weizenbaum J., Computer Power and Human Reason, W.H. Freeman and Co., San Francisco, 1976.