刘宏兵, 柳春华. 用于手写数字识别的增量式模糊支持向量机[J]. 信阳师范学院学报(自然科学版), 2014, 27(3): 421-424. DOI: 10.3969/j.issn.1003-0972.2014.03.029
引用本文: 刘宏兵, 柳春华. 用于手写数字识别的增量式模糊支持向量机[J]. 信阳师范学院学报(自然科学版), 2014, 27(3): 421-424. DOI: 10.3969/j.issn.1003-0972.2014.03.029
Liu Hongbing , Liu Chunhua. Incremental Fuzzy Support Vector Machines for Handwritten Digit Recognition[J]. Journal of Xinyang Normal University (Natural Science Edition), 2014, 27(3): 421-424. DOI: 10.3969/j.issn.1003-0972.2014.03.029
Citation: Liu Hongbing , Liu Chunhua. Incremental Fuzzy Support Vector Machines for Handwritten Digit Recognition[J]. Journal of Xinyang Normal University (Natural Science Edition), 2014, 27(3): 421-424. DOI: 10.3969/j.issn.1003-0972.2014.03.029

用于手写数字识别的增量式模糊支持向量机

Incremental Fuzzy Support Vector Machines for Handwritten Digit Recognition

  • 摘要: 根据不同训练样本对于训练过程具有不同的贡献度,构造增量函数.通过设置增量函数的阈值,构造了用于手写数字识别的增量式模糊支持向量机.选取机器学习与智能系统中心的手写数字识别问题来验证文中方法的优越性,与模糊支持向量机相比,文中方法加快了训练过程,提高了识别精度.

     

    Abstract: According to different contributions for different samples during training process, the incremental function was formed. The incremental fuzzy support vector machine for handwritten digit recognition was constructed by the threshold of incremental function. The handwritten digit recognition selected from Center for Machine Learning and Intelligent Systems was used to verify the superiority of the proposed algorithm. Compared with fuzzy support vector machine, the incremental fuzzy support vector machine speeded up the training process and improved the recognition accuracy.

     

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