ML Anthology

Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract)

Nikolay I. Nikolaev, Evgueni N. Smirnov
ECML-PKDD 1995 pp. 327-330
doi:10.1007/3-540-59286-5_79 /ecmlpkdd/1995/nikolaev1995ecml-analytical/

Abstract

An approach to integration of the analytical and empirical learning strategies for solving the theory-based concept specialization problem is proposed. The emphasis is on learning correct concepts within conjunctive description language isolated from supplied domain theory. In order to overcome expressive limitations of such language, the analytical learning component is guided by a specific empirical version space technology. The approach learns incrementally a correct pure conjunctive or DNF concept definition in dependance on the domain theory.

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Cite

Text

Nikolaev and Smirnov. "Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract)." European Conference on Machine Learning, 1995. doi:10.1007/3-540-59286-5_79

Markdown

[Nikolaev and Smirnov. "Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract)." European Conference on Machine Learning, 1995.](https://mlanthology.org/ecmlpkdd/1995/nikolaev1995ecml-analytical/) doi:10.1007/3-540-59286-5_79

BibTeX

@inproceedings{nikolaev1995ecml-analytical,
  title     = {{Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract)}},
  author    = {Nikolaev, Nikolay I. and Smirnov, Evgueni N.},
  booktitle = {European Conference on Machine Learning},
  year      = {1995},
  pages     = {327-330},
  doi       = {10.1007/3-540-59286-5_79},
  url       = {https://mlanthology.org/ecmlpkdd/1995/nikolaev1995ecml-analytical/}
}