caa a22 4500 463207246 CHVBK 20180405153129.0 cr unu---uuuuu 170326e20070801xx s 000 0 eng 10.1007/s10462-009-9096-7 doi (NATIONALLICENCE)springer-10.1007/s10462-009-9096-7 On metricity of two heterogeneous measures in the presence of missing values [Elektronische Daten] [Martti Juhola, Jorma Laurikkala] Heterogeneous Euclidean-overlap metric and heterogeneous value difference metric given in machine learning literature are useful for the consideration of mixed-type data for machine learning, pattern recognition and data mining tasks. Mixed-type variables are quite common in practical problems, but this property has been taken into account only seldom in pattern recognition, data mining and decision making algorithms. We observed that these two distance measures are not actually metrics after having found a special situation when they are not metric, but pseudometric, a feature to be noted while using them. Nevertheless, by changing their definitions somewhat, it is possible to meet the metricity. Especially in medical applications, the redefinition of the two measures might be important, since otherwise it is possible in theory that, for example, two identical cases would be classified differently. Nearest neighbor searching tests with medical data were run to illustrate the behavior of these measures. Notwithstanding the violation of the metricity their original forms yielded slightly better classification results. The reason was that in real data sets tested there were very few almost similar cases according to these distance measures, and the original forms based on more separating distances than the redefinitions were slightly better in the classification. Springer Science+Business Media B.V., 2009 Metric nationallicence Distance nationallicence Mixed-type variables nationallicence Missing values nationallicence Medical data nationallicence Juhola Martti Department of Computer Sciences, University of Tampere, 33014, Tampere, Finland aut Laurikkala Jorma Department of Computer Sciences, University of Tampere, 33014, Tampere, Finland aut Artificial Intelligence Review Springer Netherlands 28/2(2007-08-01), 163-178 0269-2821 28:2<163 2007 28 10462 https://doi.org/10.1007/s10462-009-9096-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10462-009-9096-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Juhola Martti Department of Computer Sciences, University of Tampere, 33014, Tampere, Finland aut NATIONALLICENCE 700 1- Laurikkala Jorma Department of Computer Sciences, University of Tampere, 33014, Tampere, Finland aut NATIONALLICENCE 773 0- Artificial Intelligence Review Springer Netherlands 28/2(2007-08-01), 163-178 0269-2821 28:2<163 2007 28 10462 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer