Convex Hull Ensemble Machine Yongdai Kim   View Paper (PDF)   Return to Main-Track Regular Papers Abstract We propose a new ensemble algorithm called "Convex Hull Ensemble Machine (CHEM)." CHEM in Hilbert space is developed first and it is modified to regression and clas-sification problems. Empirical studies show that in classi-fication problems CHEM has similar prediction accuracy as AdaBoost, but CHEM is much more robust to output noise. In regression problems, CHEM works competitively with other ensemble methods such as Gradient Boost and Bagging. DiSC'03 © 2003 Association for Computing Machinery