Abstract
Comparing empirical distributions is one of the fundamental tasks in data analysis. We start with a survey of existing statistical approaches to this problem. The current numeric methods are shown to suffer from several limitations, including restrictive assumptions about the underlying distributions and non-use of available domain knowledge. These limitations can be partially overcome via the time-consuming visual examination of frequency histograms by a human expert. In this paper, we present a fuzzy-based method for automating the process of comparing frequency histograms. Our approach builds upon a novel concept of automated perceptions, introduced in our previous work. We use the evolving approach of type-2 fuzzy logic for representing the domain knowledge of human experts. The proposed method provides an automated interpretation of the differences between histogram plots, based on a cognitive model of human perception. The perception-based approach to comparison of frequency histograms is demonstrated on several samples of real-world data.
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© 2002 Springer-Verlag Berlin Heidelberg
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Last, M., Kandel, A. (2002). Fuzzy Comparison of Frequency Distributions. In: Grzegorzewski, P., Hryniewicz, O., Gil, M.Á. (eds) Soft Methods in Probability, Statistics and Data Analysis. Advances in Intelligent and Soft Computing, vol 16. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1773-7_21
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DOI: https://doi.org/10.1007/978-3-7908-1773-7_21
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1526-9
Online ISBN: 978-3-7908-1773-7
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