Classification Issue in the IVF ICSI/ET Data Analysis: Early Treatment Outcome Prognosis
By: Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewsk, Jan Czerniecki and Sławomir Wołczyński
Open Access
|Dec 2013References
- Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5-32.
- Liaw, A., & Wiener, M. (2002). Classification and Regression by randomForest. R News, 2 (3), 18-22.
- Meyer, D., Dimitriadou, E., Hornik, K., Weingessel, A., & Leisch F. (2012). e1071: Misc Functions of the Department of Statistics (e1071), TU Wien. R package version 1.6-1. Retrieved from http://CRAN.R-project.org/package=e1071.
- Milewski, R., Malinowski, P., Milewska, A. J., Ziniewicz, P., Czerniecki, J., Pierzyński, P., & Wołczyński S. (2012). Classification issue in the IVF ICSI/ET data analysis. Studies in Logic, Grammar and Rhetoric, 29(42), 75-85.
- 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, 25(38), 49-57.
- Milewski, R., Malinowski, P., Milewska, A. J., Ziniewicz, P., & Wołczyński, S. (2010). The usage of margin-based feature selection algorithm in IVF ICSI/ET data analysis. Studies in Logic, Grammar and Rhetoric, 21(34), 35-46.
- 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.
- Milewski, R., Milewska, A. J., Domitrz, J., & Wołczyński, S. (2008). In vitro fertilization ICSI/ET in women over 40. Przegląd Menopauzalny, 7(2), 85-90.
- 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.
- Radwan, J. (2011). Epidemiologia niepłodności. In J. Radwan, & S. Wołczyński (Eds.), Niepłodność i rozrod wspomagany (pp. 11-14). Poznań: Termedia.
- Stekhoven, D. J., & B¨uhlmann, P. (2012a). MissForest non-parametric missing value imputation for mixed-type data. Bioinformatics, 1(28), 112-118.
- Stekhoven, D. J., & B¨uhlmann, P. (2012b). missForest: Nonparametric Missing Value Imputation using Random Forest R package version 1.3. Retrieved from http://CRAN.R-project.org/package=missForest.
- Templ, M., Alfons, A., Kowarik, A. & Prantner, B. (2013). VIM: Visualization and Imputation of Missing Values. R package version 3.0.3.1. Retrieved from http://CRAN.R-project.org/package=VIM.
DOI: https://doi.org/10.2478/slgr-2013-0034 | Journal eISSN: 2199-6059 (formerly 0860-150X) | Journal ISSN: 0860-150X
Language: English
Page range: 103 - 115
Published on: Dec 31, 2013
Published by: University of Białystok
In partnership with: Paradigm Publishing Services
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© 2013 Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewsk, Jan Czerniecki, Sławomir Wołczyński, published by University of Białystok
This work is licensed under the Creative Commons License.