1732-3916 Mixture of Metrics Optimization for Machine Learning Problems Wiercioch Magdalena author Śmieja Marek author Uniwersytet Jagielloński w Krakowie, Polska, ul. Gołębia 24, 31-007 Kraków Correspondence to: Magdalena Wiercioch magdalena.wiercioch@ii.uj.edu.pl Correspondence to: Marek Śmieja marek.smiejag@ii.uj.edu.pl 11 04 2016 Volume 24 2015 83 92 Copyright © 2016 2016 <p style="text-align: left;">The selection of data representation and metric for a given data set is one of the most crucial problems in machine learning since it affects the results of classification and clustering methods. In this paper we investigate how to combine a various data representations and metrics into a single function which better reflects the relationships between data set elements than a single representation-metric pair. Our approach relies on optimizing a linear combination of selected distance measures with use of least square approximation. 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