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A Fast Incremental SVM algorithm for discovery of CCPs on HACCP Implementation

机译:一种快速增量SVM算法,用于发现HACCP实现中的CCPS

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SVM has already shown its successful application on the CCP discovery for HACCP implementation. However, the classic non-incremental SVM method is not an efficient algorithm due to the thoroughly re-study for those samples are gradually added. In this paper, we propose a new incremental SVM algorithm d-ISVM which makes use of the heuristic that training should be firstly applied on cases which have greater possibilities to be SVs, so the training set can be reduced. The experiments show that the training speed is visibility improved without losing the precision of the classification.
机译:SVM已经显示其成功应用于HACCP实现的CCP发现。然而,经典的非增量SVM方法不是由于逐渐添加这些样本的彻底重新研究,而不是一个有效的算法。在本文中,我们提出了一种新的增量SVM算法D-ISVM,它利用培训的启发式训练应该在具有更大可能性SV的情况下应用训练,因此可以减少训练集。实验表明,训练速度是可见性改善而不会失去分类的精度。

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