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Abstract: In the present paper we propose an approach to inductive machine learning based on a consistent integration of the generalizationbased (such as inductive learning from examples) and metric-based (such as agglomerative clustering) approaches. The approach stems from the natural idea (formally studied within the lattice theory) to estimate the similarity between two objects in a hierarchical structure by the distances to their closest common parent. The hierarchies used are the subsumption ... (Update)
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BibTeX entry: (Update)
Z. Markov and N. Pelov, A framework for inductive learning based on subsumption lattices, Proceedings of AIMSA'98, ed. F. Guinchiglia, Lecture Notes in Artificial Intelligence 1480, Springer (1998) 341--352. http://citeseer.ist.psu.edu/markov98framework.html More
@article{ markov98framework,
author = "Zdravko Markov and Nikolay Pelov",
title = "A Framework for Inductive Learning Based on Subsumption Lattices",
journal = "Lecture Notes in Computer Science",
volume = "1480",
pages = "341--??",
year = "1998",
url = "citeseer.ist.psu.edu/markov98framework.html" }
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328 Algorithmic program debugging (context) - Shapiro - 1983
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267 A note on inductive generalization (context) - Plotkin - 1970
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103 Model of incremental concept formation (context) - Gennari, Langley et al. - 1990
63 Transformational systems and the algebraic structure of atom.. (context) - Reynolds - 1970
58 Learning by being told and learning from examples: An experi.. (context) - Michalski, Chilausky - 1980
17 Metrics on terms and clauses (context) - Hutchinson - 1997
11 Complexity-based induction - Conklin, Witten - 1994
5 Empirically conservative search space reduction (context) - Champesme, Br'ezellec et al. - 1995
5 An Analysis of Refinement Operators in Inductive Logic Progr.. (context) - van der Laag - 1995
5 Metrics on partially ordered sets -- a survey (context) - Monjardet - 1981
[Article contains additional citations not shown here]
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