An Integration of Extreme Learning Machine for Classification of Big Data

DOI

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.

Copyright

© 2013, 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/).

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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  - Proceedings of 2013 International Conference on Information Science and Computer Applications
PB  - Atlantis Press
SP  - 81
EP  - 86
SN  - 1951-6851
UR  - https://doi.org/10.2991/isca-13.2013.14
DO  - 10.2991/isca-13.2013.14
ID  - Zhou2013/10
ER  -