1. Amaratunga, D., Cabrera, J., & Kovtun, V. (2008). Microarray learning with ABC. Biostatistics, 9, 128–136.
2. Asuncion, A., & Newman, D. J. (2007). UCI machine learning repository. University of California, Irvine, School of Information and Computer Science.
http://www.ics.uci.edu/~mlearn/MLRepository.html
.
3. Banfield, R., Bowyer, K., Kegelmeyer, W., & Hall, L. (2007). A comparison of decision tree ensemble creation techniques. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 173–180.
4. Bauer, E., & Kohavi, R. (1999). An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 36, 105–139.
5. Boulesteix, A. L., Janitza, S., Kruppa, J., & König, I. R. (2012). Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2, 496.