Funder
National Institute of Environmental Health Sciences
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition
Reference34 articles.
1. Breiman, L.: Bagging predictors. Machine Learning 24(2), 123–140 (1996). DOI: https://doi.org/10.1007/bf00058655
2. Breiman, L.: Random forests. Machine Learning 45(1), 5–32 (2001). DOI: https://doi.org/10.1023/A:1010933404324
3. Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Chapman & Hall, New York. http://www.crcpress.com/catalog/C4841.htm
4. Bryll, R., Gutierrez-Osuna, R., Quek, F.: Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets. Pattern Recognition 36(6), 1291–1302 (2003)
5. Chen T, Guestrin C (2016) Xgboost: A scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pp. 785–794. https://doi.org/10.1145/2939672.2939785
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