The Management of Context-Sensitive Features: A Review of Strategies

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ConferenceProceedings of the Workshop on Learning in Context-Sensitive Domains,at the 13th International Conference on Machine Learning (ICML-96), July 3-6, 1996., Bari, Italy
AbstractIn this paper, we review five heuristic strategies for handling context-sensitive features in supervised machine learning from examples. We discuss two methods for recovering lost(implicit) contextual information. We mention some evidence that hybrid strategies can have a synergetic effect. We then show how the work of several machine learning researchers fits into this framework. While we do not claim that these strategies exhaust the possibilities, it appears that the framework includes all of the techniques that can be found in the published literature on context-sensitive learning.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number39221
NPARC number8914206
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Record identifiera3d4a740-5d11-46be-95ff-81e372cb23ba
Record created2009-04-22
Record modified2016-05-09
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