An integrated framework for empirical discovery-Reference-Cited by-同舟云学术

An integrated framework for empirical discovery

Published:1993-08 Issue:1-3 Volume:12 Page:17-47
ISSN:0885-6125
Container-title:Machine Learning
language:en
Short-container-title:Mach Learn

Author:

Nordhausen Bernd,Langley Pat

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/BF00993059.pdf

Reference32 articles.

1. DeCoste, D. (1991). Dynamic across-time measurement interpretation.Artificial Intelligence, 51, 273?341.

2. Emde, W., Habel, C., & Rollinger, C. (1983). The discovery of the equator or concept driven learning.Proceedings of the Eighth International Joint Conference on Artificial Intelligence (pp. 455?458). Karlsruhe, West Germany: Morgan Kaufmann.

3. Falkenhainer, B.C., & Michalski, R.S. (1986). Integrating quantitative and qualitative discovery: TheAbacus system.Machine Learning, 1, 367?422.

4. Falkenhainer, B.C., & Rajamoney, S. (1988). The interdependencies of theory formation, revision, and experimentation.Proceedings of the Fifth International Conference on Machine Learning (pp. 353?366). Ann Arbor, MI: Morgan Kaufmann.

5. Fisher, D. (1987). Knowledge acquisition via incremental conceptual clustering.Machine Learning, 2, 139?172.

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