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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/1038

Title: Data characteristics that determine classifier performance
Authors: Van der Walt, C
Barnard, E
Keywords: Data classifier performance
Datasets
Non-parametric classifiers
Issue Date: Nov-2006
Citation: Van der Walt, C and Barnard, E. 2006. Data characteristics that determine classifier performance. 17th Annual Symposium of the Pattern Recognition Association of South Africa, Parys, South Africa, 29 Nov - 1 Dec 2006, pp 6
Abstract: The relationship between the distribution of data, on the one hand, and classifier performance, on the other, for non-parametric classifiers has been studied. It is shown that predictable factors such as the available amount of training data (relative to the dimensionality of the feature space), the spatial variability of the effective average distance between data samples, and the type and amount of noise in the data set influence such classifiers to a significant degree. The methods developed here can be used to gain a detailed understanding of classifier design and selection.
Description: This paper is published in the SAIEE Africa Research Journal, Vol 98(3), pp 87-93
URI: http://hdl.handle.net/10204/1038
Appears in Collections:Human language technologies
General science, engineering & technology

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