Abstract
In order to improve the quantitative performance appraisal mechanism in the existing innovation and Entrepreneurship Talent Management System, a research scheme based on data mining technology is proposed. The combination of decision tree algorithm and cluster analysis is applied to the quantitative performance appraisal system, so as to explore the relationship between the appraisal results and various factors. Kmeans clustering algorithm is used to evaluate and analyze the team members, which is roughly divided into four levels in the form of classification rules. According to the evaluation level and the core attributes of entrepreneurial team, the detailed final individual quantitative assessment score table is generated by using the decision tree algorithm. Taking the actual data of an entrepreneurial team as the sample to test, analyze and verify, the test results show that the proposed scheme has better accuracy, and provides strong decision support for talent team management.
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Qiu, S. (2022). Multiple Evaluation System of Cloud Computing Quality. In: Macintyre, J., Zhao, J., Ma, X. (eds) The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIoT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-030-89508-2_34
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