Cascade classifiers for multiclass problems
Pablo M. Granitto, Alejandro Rébola, U. Cerviño, Flavia Gasperi, Franco Biasioli, H. A. Ceccatto · 2005
Abstract. We discuss a cascade approach to multiclass classification problems which breaks the original task into smaller subproblems in a divide-andconquer strategy. We use a splitting strategy based on the confusion matrix associated to the first (primary) classifier of the cascade, sorting test samples into independent problems according to the columns of this matrix. We test all possible combinations of three state-of-the-art classification algorithms, applying them alternatively in the two stages of the method. Performances of all these combined classifiers are evaluated on 7 real-world datasets. 1