孤立点挖掘在高等学校科技统计数据分析中的应用

Application of outlier mining in science and technology statistics data analysis

孤立点挖掘是一项有价值的、重要的知识发现,研究孤立点的异常行为能发现隐藏在数据中有价值的信息。本文在介绍孤立点及其挖掘算法的基础上,讨论了基于距离和的孤立点挖掘算法,并将该算法创新地应用于高等学校科技统计数据分析中。结果表明,该算法可以有效地挖掘出高等学校科技统计数据中的异常现象,对数据的真实性的核对起到非常重要的作用。

Outlier mining is a meaningful and important knowledge discovery task,valuable information hidden in data is found by researching the abnormal behaviors of the outliers.In the paper,the knowledge of outlier and the algorithms for detecting outliers are introduced;an algorithm based on distance sum is discussed to solve science and technology statistics data analysis of colleges and universities.The results of example indicate that the algorithm can effectively dig out the abnormal phenomenon and it is very important for the check of data.