基于网格划分的高维大数据集离群点检测算法研究

Research on the Outlier Detection Algorithm of High-Dimensional Data Set Based on the Grid Partition

数据挖掘技术的快速发展,有效带动了各个领域的发展,而离群点检测技术,作为数据挖掘技术中的重要组成,自然也成为了社会各界关注的主要课题之一。该检测方式属于数据挖掘知识中的重要研究方向,像电子商务欺诈行为检测等,都属于其检测范畴。论文将重点就以网格划分为基础的高维大数据集离群点检测算法展开深度研究,期望能够为国内离群点研究工作发展,提供一定助力。

The rapid development of data mining technology has effectively promoted the development of various fields.And the outlier detection technology,as an important component of data mining technology,has become one of the main topics of attention from all walks of life.The detection method belongs to the important research direction in the data mining knowledge,such as the detection of electronic commerce fraud and so on,which all belong to the detection category.This paper will focus on the depth study of high-dimensional large data set outlier detection algorithm based on grid division,hoping to provide some help for the development of outlier research in China.