Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)

Research on incomplete data mining and filling algorithm during depth learning process

Authors
Liping Wang
Corresponding Author
Liping Wang
Available Online February 2017.
DOI
10.2991/meita-16.2017.67How to use a DOI?
Keywords
Depth learning; missing data filling; automatic coding
Abstract

In this paper, an incomplete data padding algorithm based on depth learning is proposed. The algorithm has a rich information dimension for large data. A depth-filling network is constructed to extract the depth features of large data, and then the missing values are restored. Experimental results showed that the algorithm proposed in this paper can effectively improve the accuracy of data filling. To solve this problem, this paper proposes an incomplete data filling algorithm based on depth learning. The algorithm is based on the automatic coding machine to establish the automatic filling machine. On this basis, a deep-filling network model is constructed to analyze the depth characteristics of incomplete data and calculate the network parameters according to the layer-by-layer training idea and back propagation algorithm. Finally, the incomplete data is restored by deep filling network, and the missing value is filled. In the next step, we explore how to improve the data filling accuracy in multi-miss mode.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
Series
Advances in Engineering Research
Publication Date
February 2017
ISBN
10.2991/meita-16.2017.67
ISSN
2352-5401
DOI
10.2991/meita-16.2017.67How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liping Wang
PY  - 2017/02
DA  - 2017/02
TI  - Research on incomplete data mining and filling algorithm during depth learning process
BT  - Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
PB  - Atlantis Press
SP  - 325
EP  - 329
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-16.2017.67
DO  - 10.2991/meita-16.2017.67
ID  - Wang2017/02
ER  -