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Hausdorff Distance-Based Binary Search Tree Multiclass Decomposition Algorithm

机译:豪斯多夫距离基二元搜索树多字母分解算法

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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.
机译:多标准分解算法是二进制分类算法,如支持向量机,用于多字母分类问题的方法。 流行的多种子分解算法,如一个针对一个(OAO),一个针对所有(OAA),以天真的方式执行分解。 本文介绍了一种基于新的启发式分解算法,其两个类之间的Hausdorff距离来决定分解。 已经评估了呈现的算法,并将其与九个数据集的OAO和OAA方法进行了评估。 比较表明,呈现的方法不仅提供了可比性,而且在大多数情况下也可以将测试样本分类为较少的平均支持向量数量,从而导致更快的测试性能。

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