[Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992). A training algorithm for optimal margin classifiers, In D. Haussler (Ed.), 5th Annual ACM Workshop on COLT (pp. 144–152). Pittsburgh, PA, USA: ACM Press.]Search in Google Scholar
[Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5–32.10.1023/A:1010933404324]Search in Google Scholar
[Li, S. (2009). Random KNN Modeling and Variable Selection for High Dimensional Data. (Doctoral Dissertations, West Virginia University). Available from Proquest, Umi Dissertation Publishing (AAI3381197).]Search in Google Scholar
[Liaw, A., & Wiener, M. (2002). Classification and Regression by randomForest. R News, 2(3), 18–22.]Search in Google Scholar
[Malinowski, P., Milewski, R., Ziniewicz, P., Milewska, A. J., Czerniecki, J., & Wołczyński, S. (2013). Classification Issue in the IVF ICSI-ET Data Analysis: Early Treatment Outcome Prognosis. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 35(48), 103–115.10.2478/slgr-2013-0034]Search in Google Scholar
[Malinowski, P., Milewski, R., Ziniewicz, P., Milewska, A. J., Czerniecki, J., & Wołczyński, S. (2014). The use of data mining methods to Predict the Result of Infertility Treatment Using the IVF ET Method. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 39(52), 103–115.10.2478/slgr-2014-0044]Search in Google Scholar
[Meyer, D., Dimitriadou, E., Hornik, K., Weingessel, A., & Leisch, F. (2014). e1071: Misc Functions of the Department of Statistics (e1071), TU Wien (R package version 1.6–4). Retrieved from http://CRAN.R-project.org/package=e1071]Search in Google Scholar
[Milewska, A. J., Górska, U., Jankowska, D., Milewski, R., & Wołczyński, S. (2011). The use of the basket analysis in a research of the process of hospitalization in the gynecological ward. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 25(38), 83–98.]Search in Google Scholar
[Milewska, A. J., Jankowska, D., Citko, D., Więsak, T., Acacio, B., & Milewski, R. (2014). The use of principal component analysis and logistic regression in prediction of infertility treatment outcome. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 39(52), 7–23.10.2478/slgr-2014-0043]Search in Google Scholar
[Milewski, R., Jamiołkowski, J., Milewska, A. J., Domitrz, J., Szamatowicz, J., & Wołczyński, S. (2009). Prognosis of the IVF ICSI/ET procedure efficiency with the use of artificial Neural networks among patients of the Department of Reproduction and Gynecological Endocrinology. Ginekologia Polska, 80(12), 900–906.]Search in Google Scholar
[Milewski, R., Malinowski, P., Milewska, A. J., Czerniecki, J., Ziniewicz, P., & Wołczyński, S. (2011). Nearest neighbor concept in the study of IVF ICSI/ET treatment effectiveness. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 25(38), 49–57.]Search in Google Scholar
[Milewski, R., Milewska, A. J., Czerniecki, J., Leśniewska, M., & Wołczyński, S. (2013). Analysis of the demographic profile of patients treated for infertility using assisted reproductive techniques in 2005–2010. Ginekologia Polska, 84(7), 609–614.10.17772/gp/1612]Search in Google Scholar
[Milewski, R., Milewska, A. J., Więsak, T., & Morgan, A. (2013). Comparison of artificial neural networks and logistic regression analysis in pregnancy prediction using in the in vitro fertilization treatment. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 35(48), 39–48.10.2478/slgr-2013-0033]Search in Google Scholar
[Oba, S., Sato, M., Takemasa, I., Monden, M., Matsubara, K., & Ishii, S. (2003). A Bayesian missing value estimation method for gene expression profile data. Bioinformatics, 19(16), 2088–2096.10.1093/bioinformatics/btg287]Search in Google Scholar
[Radwan, J. (2011). Epidemiologia niepłodności. In J. Radwan, & S. Wołczyński (Eds.), Niepłodność i rozród wspomagany (pp. 11–14). Poznań, Polska: Termedia.]Search in Google Scholar
[Stekhoven, D. J., & Bühlmann, P. (2012). MissForest – non-parametric missing value imputation for mixed-type data. Bioinformatics, 1(28), 112–118.10.1093/bioinformatics/btr597]Search in Google Scholar
[Stekhoven, D. J. (2013). missForest: Nonparametric Missing Value Imputation using Random Forest (R package version 1.4). Retrieved from http://CRAN.R-project.org/package=missForest]Search in Google Scholar
[Templ, M., Alfons, A., Kowarik, A., & Prantner, B. (2015). VIM: Visualization and Imputation of Missing Values (R package version 4.3.0). Retrieved from http://CRAN.R-project.org/package=VIM]Search in Google Scholar