An Application Based on K-Means Algorithm for Clustering Companies Listed

Abstract

There exist many customers in credit market that needs to be classified into distinct groups. K-means algorithm are presented, which based on the historical financial ratios, utilizing the cluster analysis technology to analyze the listed enterprises in Zhejiang province. Some indicators related to financial attributes are analyzed, and nine finance indicators are chosen. According to better valuation on the companies listed, we apply to "try and error" and choose 4 as the number of clustering. 81 samples are divided into two groups: one training group with 60 firms and other testing group with 21 samples. Testing results shows that the model trained can be available for clustering companies listed in Zhejiang province