— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...
Abstract—We experimentally evaluate bagging and seven other randomizationbased approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed o...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
While learning ensembles have been widely used for various pattern recognition tasks, surprisingly, they have found limited application in problems related to medical image analysi...
Anant Madabhushi, Jianbo Shi, Michael D. Feldman, ...
Abstract. We describe an ensemble of classifiers based algorithm for incremental learning in nonstationary environments. In this formulation, we assume that the learner is presente...
The standard method for combating spam, either in email or on the web, is to train a classifier on manually labeled instances. As the spammers change their tactics, the performanc...
Deepak Chinavle, Pranam Kolari, Tim Oates, Tim Fin...