Cost-sensitive learning of classification knowledge and its applications in robotics-Reference-Cited by-同舟云学术

Cost-sensitive learning of classification knowledge and its applications in robotics

Published:1993-10 Issue:1 Volume:13 Page:7-33
ISSN:0885-6125
Container-title:Machine Learning
language:en
Short-container-title:Mach Learn

Author:

Tan Ming

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/BF00993101.pdf

Reference30 articles.

1. Aha, D.W. (1989). Incremental, instance-based learning of independent and graded concept descriptions.Proceedings of the Sixth International Workshop on Machine Learning (pp. 387?391). Ithaca, NY: Morgan Kaufmann.

2. Aha, D.W., & Gladstone, R.L. (1990). Learning attribute relevance in context in instance-based learning algorithms.Proceedings of the Twelfth Annual Conference of the Cognitive Science Society (pp. 141?148). Cambridge, MA: Lawrence Erlbaum Associates.

3. Breiman, L., Friedman, J.H., Olsen, R.A., & Stone, C.J. (1984).Classification and regression trees. Belmont, CA: Wadsworth.

4. Chen, C.H., & Mulgaonkar, P.G. (1990). Feature-utility measures for automatic vision programming.Proceedings of the 1990 IEEE International Conference on Robotics and Automation (pp. 1840?1845). IEEE Computer Society Press.

5. Cox, L.A. (1989). Incorporating statistical information into expert classification systems to reduce classification costs.Proceedings of the Second International Workshop on Artificial Intelligence and Statistics (pp. 9.1?9.11). Fort Lauderdale, FL:

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