20.500.12556/RUL-131260 Quadratic mutual information feature selection We propose a novel feature selection method based on quadratic mutual information which has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct estimation of quadratic mutual information from data samples using Gaussian kernel functions, and can detect second order non-linear relations. Its main advantages are: (i) unified analysis of discrete and continuous data, excluding any discretization; and (ii) its parameter-free design. The effectiveness of the proposed method is demonstrated through an extensive comparison with mutual information feature selection (MIFS), minimum redundancy maximum relevance (MRMR), and joint mutual information (JMI) on classification and regression problem domains. The experiments show that proposed method performs comparably to the other methods when applied to classification problems, except it is considerably faster. In the case of regression, it compares favourably to the others, but is slower. feature selection information-theoretic measures quadratic mutual information Cauchy-Schwarz divergence izbira značilk informacijsko-teoretične mere kvadratna medsebojna informacija Cauchy-Schwarzova divergenca true false true Angleški jezik Slovenski jezik Članek v reviji 2021-09-24 09:19:18 2021-09-24 09:19:19 2022-09-10 04:10:58 0000-00-00 00:00:00 2017 0 0 16 str. iss. 4, art. 157 Vol. 19 2017 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004 1099-4300 10.3390/e19040157 1537405123 RAZ_Sluga_Davor_2017.pdf RAZ_Sluga_Davor_2017.pdf 1 6E10CD9DC70A41C72A590449CB1544CD 6f039b488419b15f2c5ac7ccd6c61b2f3dfcf6ea108ad1a2109654895f0e0c28 5a7eb39e-1d08-11ec-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=148559 http://www.mdpi.com/1099-4300/19/4/157 1 76077d96-1d07-11ec-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=148558 Fakulteta za računalništvo in informatiko 0 0 0