Abstract
Feature reduction is a major preprocessing step in the analysis of high-dimensional data, particularly from biomolecular high-throughput technologies. Reduction techniques are expected to preserve the relevant characteristics of the data, such as neighbourhood relations. We investigate the neighbourhood preservation properties of feature reduction empirically and theoretically. Our results indicate that nearest and farthest neighbours are more reliably preserved than other neighbours in a reduced feature set.
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Lausser, L., Müssel, C., Maucher, M., Kestler, H.A. (2012). Feature Reduction and Nearest Neighbours. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_37
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DOI: https://doi.org/10.1007/978-3-642-24466-7_37
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Online ISBN: 978-3-642-24466-7
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