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ICANN
2009
Springer

Classification Based on Combination of Kernel Density Estimators

11 years 5 months ago
Classification Based on Combination of Kernel Density Estimators
Abstract. A new classification algorithm based on combination of kernel density estimators is introduced. The method combines the estimators with different bandwidths what can be interpreted as looking at the data with different "resolutions" which, in turn, potentially gives the algorithm an insight into the structure of the data. The bandwidths are adjusted automatically to decrease the classification error. Results of the experiments using benchmark data sets show promising performance of the proposed approach when compared to classical algorithms. Key words: kernel density estimation, classification, density estimators combination
Mateusz Kobos, Jacek Mandziuk
Added 19 Aug 2010
Updated 19 Aug 2010
Type Conference
Year 2009
Where ICANN
Authors Mateusz Kobos, Jacek Mandziuk
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