Evaluation Of Job Classification Based On Cluster Analysis

Currently, with the rapid development of our country’s economy, the competition between enterprises is becoming more and more fierce, especially in the field of human resources competition performance is more outstanding, human resource has become the core resources in the process of enterprise development, for enterprise, has been from the past to improve market share, lower production costs and so on aspects of transformation is to improve the efficiency of human resource management.In enterprise human resources management, job evaluation is an important work, and do the pay for the post evaluation is the key to success, job classification and evaluation is the key step in the reasonable salary system is set, the steps are reasonable or not directly related to the fairness of the pay distribution.At the same time, because of job classification and evaluation is the difficult part of the salary system setting, especially for all kinds of position is more of a kind of large companies, using scientific and reasonable position classification and evaluation method is particularly important.Now commonly used for post evaluation methods of collation, level set method, factor comparison method and evaluation method etc., each have advantages and disadvantages, disadvantages in some way too subjective sweeping, position less company suit to work.This paper intends to explore nonparametric statistical methods such as principal component analysis (pea) and "cluster analysis" method, starting from the multiple rate factor, through the principal component analysis (pea) and cluster analysis, clustering and evaluation of each post, provide theoretical basis for setting the rational salary system.