上海交通大学学报 ›› 2019, Vol. 53 ›› Issue (6): 734-740.doi: 10.16183/j.cnki.jsjtu.2019.06.015

• 学报(中文) • 上一篇    下一篇

儿童孤独症的高秩矩阵填充模型与方法

李元超,陈峰   

  1. 上海交通大学 工业工程与管理系, 上海 200240
  • 出版日期:2019-06-28 发布日期:2019-07-23
  • 通讯作者: 陈峰,男,副教授,博士生导师,E-mail:fchen@sjtu.edu.cn.
  • 作者简介:李元超(1992-),男,陕西省榆林市人,硕士生,研究方向为统计优化与矩阵填充.
  • 基金资助:
    上海交通大学医工交叉合作项目(YG2013ZD05)

High-Rank Matrix Completion Method for Autism Spectrum Disorders

LI Yuanchao,CHEN Feng   

  1. Industrial Engineering and Management, Shanghai Jiao Tong University, Shanghai 200240, China
  • Online:2019-06-28 Published:2019-07-23

摘要: 针对儿童孤独症的临床数据填补,提出了一种基于交替方向乘子(ADMM)算法的高秩矩阵填充(HRMC)算法.该算法考虑到数据中的不同参数具有不同的重要性,在算法设计时将重要参数与非重要参数赋予不同权重.在案例分析中,利用生成的测试数据寻找最优的参数配置,并且将该算法应用到实际孤独症数据的填充中, 填充结果与参数化填充方法和低秩矩阵填充方法的结果进行对比.结果显示:所提出的算法在矩阵填充精度方面显著优于其他算法,并可应用于实际的数据清洗与处理过程中.

关键词: 矩阵填充; 高秩矩阵; 交替方向乘子算法; 儿童孤独症

Abstract: To solve the clinical data recover problem of autism spectrum disorders (ASDs), a high-rank matrix completion (HRMC) algorithm based on alternating direction method of multipliers (ADMM) was proposed. Under consideration of different parameters with different significance, the important parameters and unimportant ones were attached with various weights. In a case study, test data were generated to find the optimal parameters. Furthermore, the algorithm was applied on practical ASD clinical data. The results show that the algorithm performs better in comparison with other parameterized algorithms and normal matrix completion algorithm, which indicates that it can be applied in practical data cleaning and processing.

Key words: matrix completion; high-rank matrix; alternating direction method of multipliers (ADMM) algorithm; autism spectrum disorders (ASDs)

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