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Parallel classifiers ensemble with hierarchical machine learning for imbalanced classes
2008
2008 International Conference on Machine Learning and Cybernetics
Imbalanced distributions and mis-classified costs of two classes made conventional classification methods suffered. This paper proposed a new fast parallel classification method for imbalanced classes. Considering imbalanced distributions, the approach adopted a fast simple classifier with less features input working parallel with a complicated one. Most samples would be correctly recognized by the first classifier, and the second relatively slower classifier could be ended. The second one was
doi:10.1109/icmlc.2008.4620385
fatcat:2al56wnq4jby5ckr3xz3j7s3k4