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ICANN
2010
Springer

Classification Based on Multiple-Resolution Data View

13 years 4 months ago
Classification Based on Multiple-Resolution Data View
Abstract. We examine efficacy of a classifier based on average of kernel density estimators; each estimator corresponds to a different data "resolution". Parameters of the estimators are adjusted to minimize the classification error. We propose properties of the data for which our algorithm should yield better results than the basic version of the method. Next, we generate data with postulated properties and conduct numerical experiments. Analysis of the results shows potential advantage of the new algorithm when compared with the baseline classifier. Key words: kernel density estimation, classification based on density estimation, average of density estimators
Mateusz Kobos, Jacek Mandziuk
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICANN
Authors Mateusz Kobos, Jacek Mandziuk
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