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The selection and modification of kernel functions is a very important but rarely studied problem in the field of support vector learning. However, the kernel function of a support vector machine has great influence on its performance. The kernel function projects the dataset from the original data space into the feature space, and therefore the problems which can't be done in low dimensions could...
Motivated by improving the existing decision tree performance of dealing with multi-class problems, this paper proposes a new algorithm named multi-stage decision tree (MDT). The MDT algorithm is based on the relationship between the margin of SVM hyper-planes and their generalization capability and tries to find the large margin among the clusters. First the MDT algorithm converts the multi-class...
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