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- W2488689736 abstract "In order to analyze the teaching evaluation data effectively, based on the diversity of the weight of different evaluation indexes, this paper focuses on the issue of the current evaluation index weight setting, the method of combined weight distribution is proposed. In order to improve the accuracy of clustering, the weight is introduced to the nearest neighbor K-medoids clustering algorithm. The experimental results of UCI data set and the teaching evaluation data show that the proposed algorithm is feasible and effective in the teaching evaluation data analysis. 一种改进的聚类方法在教学评价中的应用研究" @default.
- W2488689736 created "2016-08-23" @default.
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- W2488689736 date "2016-01-01" @default.
- W2488689736 modified "2023-09-23" @default.
- W2488689736 title "Application and Research on an Improved Clustering Method in Teaching Evaluation" @default.
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- W2488689736 doi "https://doi.org/10.2991/icemc-16.2016.220" @default.
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