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Abstract: Meta-learning, as applied to model selection, consists of inducing mappings from tasks to learners. Traditionally, tasks are characterised by the values of pre-computed meta-attributes, such as statistical and information-theoretic measures, induced decision trees' characteris- tics and/or landmarkers' performances. In this position paper, we propose to (meta-)learn directly from induced decision trees, rather than rely on a hand-crafted set of pre-computed characteristics. Such... (Update)
Context of citations to this paper: More
.... Other proposals focus on using properties of the concepts that are learned with certain algorithms [1] or even the concepts themselves [3]. Landmarking tries to model the practitioner who familiarizes herself with a new problem by first trying a few fast and familiar...
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BibTeX entry: (Update)
Hilan Bensusan, Christophe Giraud-Carrier, and Claire Kennedy. A higher-order approach to meta-learning. In Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination, pages 109--117. ECML'2000, June 2000. http://citeseer.ist.psu.edu/article/bensusan00higherorder.html More
@inproceedings{ bensusan00higherorder,
author = "H. Bensusan and C. Giraud-Carrier and C. J. Kennedy",
title = "A Higher-order Approach to Meta-Learning",
booktitle = "Proceedings of the Work-in-Progress Track at the 10th International Conference on Inductive Logic Programming",
editor = "J. Cussens and A. Frisch",
pages = "33--42",
year = "2000",
url = "citeseer.ist.psu.edu/article/bensusan00higherorder.html" }
Citations (may not include all citations):89 Machine Learning (context) - Michie, Spiegelhalter et al. - 1994
56 Generalizing from Case Studies: A Case Study - Aha - 1992
39 Programming in an Integrated Functional and Logic Language - Lloyd - 1999
31 Strongly-Typed Inductive Concept Learning - Flach, Giraud-Carrier et al. - 1998
14 Meta-learning by Landmarking Various Learning Algorithms - Pfahringer, Bensusan et al. - 2000
12 God doesn't always shave with Occam's Razor - learning when .. - Bensusan - 1998
11 Classification of Individuals with Complex Structure - Bowers, Giraud-Carrier et al. - 2000
9 Automatic Bias Learning; An Inquiry into the Inductive Bias .. - Bensusan - 1999
6 A Framework for Higher-Order Inductive Machine Learning - Bowers, Giraud-Carrier et al. - 1997
6 An Evolutionary Approach to Concept Learning with Structured.. - Kennedy, Giraud-Carrier - 1999
5 An Unifying View of Knowledge Representation for Inductive L.. - Bowers, Giraud-Carrier et al. - 2000
5 Theusinger (1998). Using a Data Metric for Offering Preproce.. (context) - Engels - 1998
3 Strongly Typed Evolutionary Programming - Kennedy - 2000
2 Knowledge Representation (context) - Lloyd - 2000
2 The Effect of Data Character on Empirical Concept Learning (context) - Rendell, Cho - 1990
2 Inducing Classification Rules from Highly-structured Example.. (context) - MacKinney-Romero, Giraud-Carrier - 2000
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