改进的k均值算法在高校绩效工资分类管理中的应用研究

Studies the improved k-means clustering algorithm and proposes a new method to find the initial clustering centers. Searching initial clustering centers based on distance and density avoids calculating distance values between objects repeatedly and increases accuracy rate of clustering. Then develops an high school performance grade decision support system. The decision support system uses the improved k-means clustering algorithm to get performance pay grade standards. Finally, the result and analysis are given at the last of the paper.