基于数据挖掘分类的创新创业团队管理考核机制研究

Research on data mining classification based management and evaluation mechanism of innovation and entrepreneur team

为了对现有创新创业人才管理体系中的量化绩效考核机制进行改进,提出一种基于数据挖掘技术的研究方案。将决策树算法与聚类分析相结合运用到量化绩效考核体系中,从而发掘考核结果与各种因素之间的关系。采用K.means聚类算法对团队成员进行测评分析,以分类规则的形式粗略划分为4个等级。采用ID3决策树算法根据测评等级和创业团队核心属性,生成细化的最终个人量化考核得分表。以某个创业团队的实际数据为样本进行测试、分析和验证,测试结果表明提出方案具有较好的准确率,为人才队伍管理提供了有力的决策支持。

In order to improve the quantitative performance appraisal mechanism in the existing innovation and entrepreneur talents management system,a research plan based on data mining technology is proposed.The decision tree algorithm and cluster analysis are combined to apply to the quantitative performance appraisal system,so as to explore the relationship between the assessment results and various factors.The K-means clustering algorithm is used to evaluate and analyze the team members,and the members are roughly divided into four levels in the form of classification rules.The ID3 decision tree algorithm is used to generate a refined final score table of personal quantitative assessment,which is based on the evaluation level and the core attributes of the entrepreneur team.The actual data of a entrepreneur team was taken as a sample for testing,analysis and verification.The test results show that the proposed scheme has high accuracy rate,and provides powerful decision support for the talent team management.