计算机应用与软件2016，Vol.33Issue(10)：243-246,4.DOI:10.3969/j.issn.1000-386x.2016.10.054
一种基于极限学习机的缺失数据填充方法
A METHOD FOR MISSING DATA IMPUTATION BASED ON EXTREME LEARNING MACHINE
摘要
Abstract
In data processing process the problems of having to impute incomplete data are often encountered,so it is important to look for a simple and effective missing data imputation method.In view of this,the paper presents an extreme learning machine-based method for missing data imputation.Based on extreme learning machine modelling it builds a nonlinear mapping model of missing attributes with the need of imputation as well as other attributes.Experimental result shows that the new algorithm has excellent performance in imputation.关键词
极限学习机/缺失数据填充/UCI机器学习数据库Key words
Extreme learning machine/Missing data imputation/UCI machine learning database分类
信息技术与安全科学引用本文复制引用
杨毅,卢诚波..一种基于极限学习机的缺失数据填充方法[J].计算机应用与软件,2016,33(10):243-246,4.基金项目
国家自然科学基金项目（11171137）；浙江省自然科学基金项目（LY13A010008）。 （）
