基于聚类分析和神经网络模型对平均工资研究

Based on average wage of class average clustering analysis method and neural network model of the research

针对就业人员平均工资作分析研究,分析了传统类平均聚类分析法分类层次问题,通过不一致系数最终确定了分类层次,提出神经网络模型进行聚类分析,运用MATLAB工具箱,给出了分类层次和优劣判断方法。两种算法后者更加符合宏观实际,为解决同等问题提供了有效参考。

Average wage for employment has made the analysis and research, analyzes the traditional class average classification hierarchy clustering analysis problem, through the inconsistency coefficient finally determines the classification level, put forward neural network model for clustering analysis, using MATLAB toolbox, classification level and quality judgment method is given. Two algorithms which more accords with the practice of the macro, provides effective reference for solving the same problems.