참고문헌
- Asuncion, A. and Newman, D. J. (2007). UCI machine learning repository. University of California, Irvine, School of Information and Computer Sciences, http://archive.ics.uci.edu/ml.
- Breiman, L., Friedman, J., Olshen, R. and Stone, C. (1984). Classification and regression trees, Chapman and Hall, New York.
- Breiman, L. (1996). Bagging predictors. Machine Learning, 24, 123-140.
- Breiman, L. (2001). Random forests. Machine Learning, 45, 5-32. https://doi.org/10.1023/A:1010933404324
- Chen, K. and Jin, Y. (2010). An ensemble learning algorithm based on lasso selection. IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS), 1, 617-620.
- Dietterich, T. G. (2000). Ensemble methods in machine learning, Springer, Berlin.
- Freund, Y. and Schapire, R. (1997). A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55, 119-139. https://doi.org/10.1006/jcss.1997.1504
- Heinz, G., Peterson, L. J., Johnson, R. W. and Kerk, C. J. (2003). Exploring relationships in body dimensions. Journal of Statistics Education, 11, http://www.amstat.org/publications/jse/v11n2/datasets.heinz.html.
- Kim, A., Kim, J. and Kim, H. (2012). The guideline for choosing the right-size of tree for boosting algorithm. Journal of the Korean Data & Information Science Society, 23, 949-959. https://doi.org/10.7465/jkdi.2012.23.5.949
- Kim, H., Kim, H., Moon, H. and Ahn, H. (2011). A weight-adjusted voting algorithm for ensemble of classifiers. Journal of the Korean Statistical Society, 40, 437-449. https://doi.org/10.1016/j.jkss.2011.03.002
- Kuncheva, L. (2004). Combining pattern classifiers: Methods and algorithms, Wiley, New Jersey.
- Kuncheva, L. (2005). Diversity in multiple classifier systems. Information Fusion, 6, 3-4. https://doi.org/10.1016/j.inffus.2004.04.009
- Loh, W.-Y. (2009). Improving the precision of classification trees. The Annals of Applied Statistics, 3, 1710-1737. https://doi.org/10.1214/09-AOAS260
- Rokach, L. (2009). Taxonomy for characterizing ensemble methods in classification tasks: A review and annotated bibliography. Computational Statistics and Data Analysis, 53, 4046-4072. https://doi.org/10.1016/j.csda.2009.07.017
- Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society B, 58, 267-288.
- Zhou, Z. H. and Tang, W. (2003). Selective ensemble of decision trees. Lecture Notes in Computer Science, 2639, 476-483.
피인용 문헌
- Tree size determination for classification ensemble vol.27, pp.1, 2016, https://doi.org/10.7465/jkdi.2016.27.1.255
- 표본코호트기반 고지혈증 약제의 저밀도 콜레스테롤 감소량 및 투약순응도 분석 vol.28, pp.5, 2017, https://doi.org/10.7465/jkdi.2017.28.5.1027
- 앙상블 기법을 이용한 가뭄지수 예측 vol.28, pp.5, 2014, https://doi.org/10.7465/jkdi.2017.28.5.1125