基于智能分类算法的数据质量检测

Data Detection Based on Intelligent Classification Algorithm

为了实现海量数据的数据检测、有效存储和后期的访问控制,设计了基于频率的数据特征值采集方法及基于支持向量机的数据智能分类算法,采用搜集来自真实数据中心应用环境的数据样本进行实验验证。结果表明,改进后的智能分类算法能达到较好的数据识别准确率,该方法具有较强的实用性,可用于机房数据质量管理和大数据分析。

In order to detect, store and control the massive data effectively, a frequency-based data eigenvalue acquisition method and an intelligent classification algorithm based on support vector machine （SVM） was designed. The experiment adopted the data samples collected from the real data center application environment. The results show that the improved intelligent classification algorithm can achieve better data recognition accuracy, and the new method has strong practica-bility, which can be used for the data quality management and big data analysis in computer room.