Spark环境下K-means初始中心点优化研究综述

In order to understand the latest research progress of the classical clustering algorithm K-means in Spark environment, and grasp the current research hotspots and directions of K-means algorithm, this paper reviews the initial center point optimization research on K-means algorithm. Firstly, it introduces the memory computing framework Spark and K-means algorithms, and analyzes the cause and effects of clustering instability of K-means algorithm, which aimed to point out the importance of optimizing K-means algorithm. And it introduces the main methods and the latest research status of optimizing the initial center point of K-means in Spark environment in detail, and also discusses the future research trends in initial center point optimization of K-means.