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Additive Groves of Regression Trees  Daria Sorokina, Rich Caruana, Mirek Riedewal
Decreasing the Randomness of Random Forests  Samuel Robert Reid - The Random Forest algorithm is an ensemble technique that can achieve high accuracy on classification and regression with minimal tuning of parameters. This paper analyzes the effectiveness of the Random Forest classification algorithm under decreasing randomness in the bootstrap sampling procedure, in increasing tournament size, and in tournament participant selection.
Improving Random Forests  Marko Robnik-ˇ Sikonja - Random forests are one of the most successful ensemble methodswhich exhibits performance on the level of boosting and support vector machines.
Using Random Forest to Learn Imbalanced Data  Chao Chen, Andy Liaw, Leo Breiman,