Incomplete Big Data Imputation Algorithm Based on Deep Learning

BU Fan-yu; CHEN Zhi-kui; ZHANG Qing-chen

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Incomplete Big Data Imputation Algorithm Based on Deep Learning

更新时间：2026-09-04

- Incomplete Big Data Imputation Algorithm Based on Deep Learning
- Vol. 31, Issue 12, Pages: 173-176(2014)
- 作者机构：
  
  1. 内蒙古财经大学机构职业学院,内蒙古,呼和浩特,010010
  2. 大连理工大学软件学院,辽宁,大连,116620
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
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卜范玉, 陈志奎, 张清辰. 基于深度学习的不完整大数据填充算法[J]. 微电子学与计算机, 2014, 31(12): 173-176.

BU Fan-yu, CHEN Zhi-kui, ZHANG Qing-chen. Incomplete Big Data Imputation Algorithm Based on Deep Learning[J]. 2014, 31(12): 173-176.
卜范玉, 陈志奎, 张清辰. 基于深度学习的不完整大数据填充算法[J]. 微电子学与计算机, 2014, 31(12): 173-176. DOI：

BU Fan-yu, CHEN Zhi-kui, ZHANG Qing-chen. Incomplete Big Data Imputation Algorithm Based on Deep Learning[J]. 2014, 31(12): 173-176. DOI：

摘要

提出一种基于深度学习的不完整大数据填充算法.算法首先以自动编码机为基础建立填充自动编码机.在此基础上

构建深度填充网络模型

分析不完整大数据的深度特征并根据逐层训练思想和反向传播算法计算网络参数.最后利用深度填充网络来还原不完整大数据

对缺失值进行填充.实验表明

提出的算法能够有效提高不完整大数据的填充精度.

Abstract

This paper presents an impuation algorithm based on learning for incomplete big data.The proposed algorithm establishs a novel auto-encoder

called imputation auto-encoder

and then builds a deep imputation network model to analyze the deep features of incomplete big data and to calculate network parameters based on drill training ideas and back-propagation algorithm.Finally

the deep imputation network is used to impute the missing values.Experimental results show that the proposed algorithm can effectively improve the imputation accuracy for incomplete big data.

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