Convex Hull Ensemble Machine
ICDM（2002）
摘要
We propose a new ensemble algorithm called "ConvexHull Ensemble Machine (CHEM)." CHEM in Hilbert spaceis developed first and it is modified to regression and clas-sificationproblems. Empirical studies show that in classi-ficationproblems CHEM has similar prediction accuracyas AdaBoost, but CHEM is much more robust to outputnoise. In regression problems, CHEM works competitivelywith other ensemble methods such as Gradient Boost andBagging.
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关键词
new ensemble algorithm,convex hull ensemble machine,similar prediction,classi-ficationproblems chem,ensemble method,regression problem,empirical study,convexhull ensemble machine,accuracy,classification,learning artificial intelligence,hilbert space,statistical analysis,regression,statistics,solid modeling,bagging,machine learning,hilbert spaces,adaboost,data mining,convex hull,decision trees,geometry
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