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Abstract: Multidimensional data is often feature space heterogeneous so that individual features have unequal importance in different sub areas of the feature space. This motivates to search for a technique that provides a strategic splitting of the instance space being able to identify the best subset of features for each instance to be classified. Our technique applies the wrapper approach where a classification algorithm is used as an evaluation function to differentiate between different feature... (Update)
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BibTeX entry: (Update)
Puuronen, S., Tsymbal, A.: Local feature selection with dynamic integration of classifiers, In: Fundamenta Informaticae, Special Issue "Intelligent Information Systems", Vol. 47, Nos.1-2, IOS Press (2001) 91-117. http://citeseer.ist.psu.edu/puuronen01local.html More
@misc{ puuronen01local,
author = "S. Puuronen and A. Tsymbal",
title = "Local feature selection with dynamic integration of classifiers",
text = "Puuronen, S., Tsymbal, A.: Local feature selection with dynamic integration
of classifiers, In: Fundamenta Informaticae, Special Issue Intelligent Information
Systems, Vol. 47, Nos.1-2, IOS Press (2001) 91-117.",
year = "2001",
url = "citeseer.ist.psu.edu/puuronen01local.html" }
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