微型电脑应用2025，Vol.41Issue(1)：58-60,64,4.
人工智能辅助下残缺数据样本集补全算法与应用
Artificial Intelligence Assisted Incomplete Data Sample Set Completion Algorithm and Its Application
摘要
Abstract
To address the issues of low accuracy and faults in estimating data values during the process of completing incomplete data sample sets due to the lack of similarity of evaluation data sample set,a new algorithm for completing the incomplete data sample set is proposed.An interpolation model is used to construct a fitting function for the incomplete data,and obtain a set of similar data samples.The Pearson correlation coefficient is used to evaluate the similarity of the similar data sample set,and obtain weights for completing the incomplete data sample set.A recommendation algorithm is used to calculate the optimal rec-ommended values,achieving the completion of the incomplete data sample set.Experimental results show that compared to ex-isting algorithms for completing incomplete data sample sets,this algorithm greatly improves the accuracy of data value estima-tion and completion rate,which fully demonstrates its superior completion performance and strong practical application capabili-ties in ensuring data integrity in various fields.关键词
人工智能/残缺/数据样本集/数据补全Key words
artificial intelligence/incompleteness/data sample set/data completion分类
信息技术与安全科学引用本文复制引用
李洋,张镝..人工智能辅助下残缺数据样本集补全算法与应用[J].微型电脑应用,2025,41(1):58-60,64,4.基金项目
吉林省教育厅科学研究项目(JJKH20231542KJ) （JJKH20231542KJ）
