一种面对大数据集的改进基于支持向量机的算法性能分析

An Improved Algorithm Performance Analysis Based on Support Vector Machine (SVM) for Large Data Sets

为了提高面对大规模数据集时,支持向量机模型的运算效率,本文构建的新模型SSVM-FCM算法。该算法精度可以达到95%以上,并且不会受到子簇数量的影响。本算法可以达到较高分类精度与良好的鲁棒性,引入吸收规则后还可以获得更高的计算精度。

In order to improve the computational efficiency of SVM model in the face of large data sets,a new model SSVM-FCM algorithm is constructed in this paper.The accuracy of the algorithm can reach above 95%and is not affected by the number of subclusters.This algorithm can achieve high classification accuracy and good robustness,and higher calculation accuracy can be achieved by introducing the absorption rule.