基于支持向量机的数据挖掘技术

Data Mining Based on Support Vector Machine

随着数据库技术的迅速发展以及数据库管理系统的广泛应用,人们积累的数据越来越多.激增的数据背后隐藏着许多重要的信息,人们希望能够对其进行更高层次的分析,以便更好地利用这些数据.将目前先进的机器学习技术—支持向量机,与数据挖掘结合起来,提出了一个改进的支持向量机训练算法,进行了支持向量机自动分类的模拟试验.试验结果显示,新算法的训练速度明显提高,并获得了比较理想的分类结果.

With rapid progress of database technology, more and more data are having been accumulated. Behind and wide use of database management systems, these proliferated data, much important information is hidden, and people hope to do high-level processing so as to make full use of them. This paper combines support vector machine, the advanced machine learning technique at present, with data mining, presents an improved SVM training algorithm, and performs a simulated experiment on SVM automated classifying. Experiments show that convergence speed the classification effect is satisfied. of the improved algorithm is remarkably faster, and the classification effect is satisfied.