随着等级测评工作的定期进行,等级测评过程中会不断产生并积累海量的测评数据,但是从以测评报告形式存在的测评数据中无法有效地提取出有价值的信息,无法为后续的等级保护工作形成参考指导.利用K-means聚类算法对等级测评数据进行了分析.首先,介绍了等级测评的概念及基本内容;然后,阐述了K-means聚类算法理论;最后,详细地介绍了基于K-means聚类算法的等级测评数据分析的具体流程,为等级测评数据的充分利用提供了一定的参考.
With the regular implementation of level evaluation,massive evaluation data will be generated and accu-mulated continuously in the process of classified protection evaluation,but valuable information cannot be effectively extracted from the evaluation data in the form of evaluation reports,and it cannot form reference guidance for subse-quent classified protection work.The classified protection evaluation data is analyzed by using K-means clustering al-gorithm.First,the concept and basic content of classified evaluation are introduced.Then,the theory of K-means clustering algorithms is elaborated.Finally,the specific process of level assessment data analysis based on K-means clustering algorithm is introduced in detail,which provides a certain reference for the full utilization of classified evalu-ation data.