Information criteria in classification: new divergence-based classifiers

References

• Fukunaga K. Introduction to statistical pattern recognition. New York: Academic Press; 1990.
   Google Scholar
• Silva WB, Freitas CC, SantAnna S, et al. Classification of segments in PolSAR imagery by minimum stochastic distances between Wishart distributions. Appl Earth Observ Remote Sens. 2013;6:1263–1273. doi: 10.1109/JSTARS.2013.2248132
   Web of Science ®Google Scholar
• Impedovo D, Pirlo G. Automatic signature verification: the state of the art. IEEE Trans Syst, Man Cybern C Appl Rev. 2008;38:609–635. doi: 10.1109/TSMCC.2008.923866
   Web of Science ®Google Scholar
• James G, Witten D, Hastie T. An introduction to statistical learning. New York: Springer; 2013.
   Google Scholar
• Hastie T, Tibshirani R, Friedman J. The elements of statistical learning. Vol. 2. New York: Springer; 2009.
   Google Scholar
• Ripley B. Pattern recognition and neural networks. 1st ed. Cambridge: Cambridge university press; 1996.
   Google Scholar
• Cover T, Hart P. Nearest neighbor pattern classification. IEEE Trans Inform Theory. 1967;13:21–27. doi: 10.1109/TIT.1967.1053964
   Web of Science ®Google Scholar
• Kullback S, Leibler RA. On information and sufficiency. Ann Math Stat. 1951;22:79–86. doi: 10.1214/aoms/1177729694
   Google Scholar
• Kullback S. Information theory and statistics. New York: Courier Dover Publications; 2012.
   Google Scholar
• Jager L, Wellner JA. Goodness-of-fit tests via phi-divergences. Ann Stat. 2007;35:2018–2053. doi: 10.1214/0009053607000000244
   Web of Science ®Google Scholar
• Toma A, Leoni-Aubin S. Robust tests based on dual divergence estimators and saddlepoint approximations. J Multivariate Anal. 2010;101:1143–1155. doi: 10.1016/j.jmva.2009.11.001
   Web of Science ®Google Scholar
• Nascimento ADC, Cintra RJ, Frery AC. Hypothesis testing in speckled data with stochastic distances. IEEE Trans Geosci Remote Sens. 2010;48:373–385. doi: 10.1109/TGRS.2009.2025498
   Web of Science ®Google Scholar
• Frery AC, Nascimento ADC, Cintra RJ. Analytic expressions for stochastic distances between relaxed complex Wishart distributions. IEEE Trans Geosci Remote Sens. 2014;52:1213–1226. doi: 10.1109/TGRS.2013.2248737
   Web of Science ®Google Scholar
• Eguchi S, Copas J. Interpreting KullbackLeibler divergence with the NeymanPearson lemma. J Multivariate Anal. 2006;97:2034–2040. doi: 10.1016/j.jmva.2006.03.007
   Web of Science ®Google Scholar
• Gersch W, Martinelli F, Yonemoto J, et al. Automatic classification of electroencephalo- grams: Kullback–Leibler nearest neighbor rules. Sciences. 1979;205:193–195. doi: 10.1126/science.451587
   PubMed Web of Science ®Google Scholar
• Shore J, Gray RM. Minimum cross-entropy pattern classification and cluster analysis. IEEE Trans Pattern Anal Mach Intel. 1982;PAMI-4:11–17. doi: 10.1109/TPAMI.1982.4767189
   Web of Science ®Google Scholar
• Mai Q, Zou H. Sparse semiparametric discriminant analysis. J Multivariate Anal. 2015;135:175–188. doi: 10.1016/j.jmva.2014.12.009
   Web of Science ®Google Scholar
• Hu Y, Zhao K, Lian H. Bayesian additive machine: classification with a semiparametric discriminant function. J Stat Comput Simul. 2016;86(4):682-–695. doi: 10.1080/00949655.2015.1028937
   Web of Science ®Google Scholar
• Mallows CL. Some comments on CP. Technometrics. 1973;15:661–675.
   Web of Science ®Google Scholar
• Seghanane AK, Amari SI. The AIC criterion and symmetrizing the Kullback–Leibler divergence. IEEE Trans Neural Netw. 2007;6:1263–1273.
   Google Scholar
• Rényi A. On measures of entropy and information. Berkeley Symp Math Stat Probab. 1961;1:547–561.
   Google Scholar
• R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing; 2014.
   Google Scholar
• Johnson RA, Wichern DW. Applied multivariate statistical analysis. Vol. 5, Prentice hall: Upper Saddle River, NJ; 2002.
   Google Scholar
• Efron B, Gong G. A leisurely look at the bootstrap, the jackknife, and cross-validation. Amer Stat. 1983;37:36–48.
   Web of Science ®Google Scholar
• Azzalini A, Valle AD. The multivariate skew-normal distribution. Biometrika. 1996;83(4):715–726. doi: 10.1093/biomet/83.4.715
   Web of Science ®Google Scholar
• Ulaby F, Elachi C. Radar polarimetry for geoscience applications. Norwood: Artech House; 1990.
   Google Scholar