Hausdorff Distance-Based Binary Search Tree Multiclass Decomposition Algorithm

Abstract

Multiclass decomposition algorithms are the means by which binary classification algorithms, like support vector machine, are used for multiclass classification problems. The popular multiclass decomposition algorithms, like one against one (OAO), one against all (OAA), perform the decomposition in a naive manner. This paper presents a novel heuristic-based decomposition algorithm that takes the Hausdorff distance between two classes to decide the decomposition. The presented algorithm has been evaluated and compared against OAO and OAA methods across nine datasets. The comparison shows that presented method not only provides comparable performance, but also in most cases can classify the test samples with fewer average number of support vectors, thus leading to faster test performance.