This paper proposes a weighted C-SVM algorithm and analyzes its classification performance theoretically.

提出了一种加权C—SVM分类算法，并从理论上分析了算法的性能。

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Thirdly, a GPU based massively data parallel C-SVM classification (GMP-CSVC) algorithm is presented to reduce the training time of SVM.

第三，针对支持向量机算法复杂度较高，难以应用于大样本分类的问题，提出了GMP-CSVC算法。

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This paper researches the parameters (kernel, penalty parameter c) of SVM and the dimension of feature, which influence aerial image segmentation and classification.

研究了支持向量机参数(核函数、惩罚因子c)和影像特征维数对航空影像分割与分类的影响。

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