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Abstract: Determinations are a useful type of functional knowledge representation. Applications include knowledge-based systems, analogical reasoning, database design, and robotic sensing systems. This paper presents an efficient, batch algorithm for inducing all minimal determinations from observed data. The algorithm is based on breadth-first search and runs in polynomial time and space given a user-supplied parameter limiting the maximum size of a determination. The algorithm uses probabilistic... (Update)
Context of citations to this paper: More
.... has been an increase in interest in the development of admissible search strategies for such classification learning tasks [6, 14, 15, 16, 18]. A search algorithm is admissible if and only if it is guaranteed to find the nominated search goal. The use of admissible search...
.... set of dependencies does not change as the number of tuples increases) To our knowledge, only one previous algorithm can claim this [13]. Previous algorithms have almost invariably been based on either repeatedly sorting the tuples of the relation or comparing every tuple to...
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BibTeX entry: (Update)
Jeffrey C. Schlimmer. Efficiently inducing determinations: A complete and systematic search algorithm that uses optimal pruning. In Proceedings of the Tenth International Conference on Machine Learning, pages 284--290, 1993. http://citeseer.ist.psu.edu/schlimmer93efficiently.html More
@inproceedings{ schlimmer93efficiently,
author = "Jeffrey C. Schlimmer",
title = "Efficiently Inducing Determinations: A Complete and Systematic Search Algorithm that Uses Optimal Pruning",
booktitle = "International Conference on Machine Learning",
pages = "284-290",
year = "1993",
url = "citeseer.ist.psu.edu/schlimmer93efficiently.html" }
Citations (may not include all citations):1359 Induction of decision trees (context) - Quinlan - 1986
125 Learning with many irrelevant features - Almuallim, Dietterich - 1991
92 An empirical comparison of selection measures for decision-t.. (context) - Mingers - 1989
31 A logical approach to reasoning by analogy (context) - Davies, Russell - 1987
24 and representation of data dependencies in databases (context) - Ziarko - 1992
6 Variability bias and category learning (context) - Martin, Billman - 1991
6 Preliminary steps toward the automation of induction (context) - Russell - 1986
4 Discovering regularities from large knowledge bases (context) - Shen - 1991
1 Learning determinations and checking databases (context) - PA, Press - 1992
1 Induction: Processes of inference (context) - Jose, AAAI et al. - 1986
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