Proceedings of 2013 International Conference on Information Science and Computer Applications

An Integration of Extreme Learning Machine for Classification of Big Data

Authors
Guanwu Zhou, Yulong Zhao, Wenju Xu
Corresponding Author
Guanwu Zhou
Available Online October 2013.
DOI
https://doi.org/10.2991/isca-13.2013.14How to use a DOI?
Keywords
data mining, extreme learning machine, back propagation neural networks, support vector machine, decision tree, big data
Abstract
Classification is an important task in data mining field. As the time of big data is coming, the traditional methods of classification cannot satisfy the requirements of real-time processing and storage for big data. This study firstly applies a machine learning technique called extreme learning machine (ELM) to classify for big data. Performances of ELM for big data are evaluated by using big data. The experimental results show that classification method based on ELM outperforms other methods based on BP neural networks and support vector machine (SVM). Secondly, the possibility of paralleling ELM based on MapReduce is analyzed and a paralleling ELM is designed.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2013 International Conference on Information Science and Computer Applications (ISCA 2013)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2013
ISBN
978-90786-77-85-7
DOI
https://doi.org/10.2991/isca-13.2013.14How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Guanwu Zhou
AU  - Yulong Zhao
AU  - Wenju Xu
PY  - 2013/10
DA  - 2013/10
TI  - An Integration of Extreme Learning Machine for Classification of Big Data
BT  - 2013 International Conference on Information Science and Computer Applications (ISCA 2013)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/isca-13.2013.14
DO  - https://doi.org/10.2991/isca-13.2013.14
ID  - Zhou2013/10
ER  -