Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset

Shuqing Lin; Feng Yin; Zhidi Lin; Yanbin Lin; Shuguang Robert Cui; Teng Li; Fengli Yu; Wei Yu; Xuemin Hong; Jianghong Shi; Zhi Quan Tom Luo

doi:10.1109/ICCChina.2018.8641222

Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset

Shuqing Lin, Feng Yin, Zhidi Lin, Yanbin Lin, Shuguang Robert Cui, Teng Li, Fengli Yu, Wei Yu, Xuemin Hong, Jianghong Shi, Zhi Quan Tom Luo

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Driven by a plethora of real machine learning applications, there have been many attempts at improving the performance of a classifier applied to imbalanced dataset. In this paper we propose a maximum entropy machine (MEM) based hybrid algorithm to handle binary classification problems with high imbalance ratios and large numbers of features in the datasets. At the training stage, we combine an efficient MEM algorithm with the SMOTE algorithm to build a classifier in a batch manner. At the application stage, the different-cost strategy is incorporated into the MEM algorithm to handle the imbalance learning problem in an online manner. Experiments are conducted based on various real datasets (including one China Mobile dataset and several other standard test datasets) with different imbalance ratios and different numbers of features. The results show that the proposed algorithm outperforms the state-of-The-Art algorithms significantly in terms of robustness and overall classification performance.

Original language	English (US)
Title of host publication	2018 IEEE/CIC International Conference on Communications in China, ICCC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	68-73
Number of pages	6
ISBN (Electronic)	9781538670057
DOIs	https://doi.org/10.1109/ICCChina.2018.8641222
State	Published - Jul 2 2018
Event	2018 IEEE/CIC International Conference on Communications in China, ICCC 2018 - Beijing, China Duration: Aug 16 2018 → Aug 18 2018

Publication series

Name	2018 IEEE/CIC International Conference on Communications in China, ICCC 2018

Conference

Conference	2018 IEEE/CIC International Conference on Communications in China, ICCC 2018
Country/Territory	China
City	Beijing
Period	8/16/18 → 8/18/18

Bibliographical note

Funding Information:
This work was supported by Shenzhen Fundamental Research Fund under Grant No. KQTD2015033114415450. The author Feng Yin was supported by Shenzhen Science and Technology Innovation Committee (KCW) project with Grant No. JCYJ20170307155957688 and NSFC with Grant No. 61701426. Feng Yin was funded by the Shenzhen Science and Technology Innovation Council with the grant number JCYJ20170307155957688 and JCYJ20170411102101881 and partly by the Shenzhen Fundamental Research Fund under Grant No. KQTD2015033114415450.

Publisher Copyright:
© 2018 IEEE.

Keywords

Binary Classification
China Mobile
Imbalanced Dataset
MEM Algorithm
Online Algorithm

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.1109/ICCChina.2018.8641222

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Cite this

Lin, S., Yin, F., Lin, Z., Lin, Y., Cui, S. R., Li, T., Yu, F., Yu, W., Hong, X., Shi, J., & Luo, Z. Q. T. (2018). Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset. In 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018 (pp. 68-73). Article 8641222 (2018 IEEE/CIC International Conference on Communications in China, ICCC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCChina.2018.8641222

Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset. / Lin, Shuqing; Yin, Feng; Lin, Zhidi et al.
2018 IEEE/CIC International Conference on Communications in China, ICCC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 68-73 8641222 (2018 IEEE/CIC International Conference on Communications in China, ICCC 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lin, S, Yin, F, Lin, Z, Lin, Y, Cui, SR, Li, T, Yu, F, Yu, W, Hong, X, Shi, J & Luo, ZQT 2018, Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset. in 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018., 8641222, 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 68-73, 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018, Beijing, China, 8/16/18. https://doi.org/10.1109/ICCChina.2018.8641222

Lin S, Yin F, Lin Z, Lin Y, Cui SR, Li T et al. Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset. In 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 68-73. 8641222. (2018 IEEE/CIC International Conference on Communications in China, ICCC 2018). doi: 10.1109/ICCChina.2018.8641222

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abstract = "Driven by a plethora of real machine learning applications, there have been many attempts at improving the performance of a classifier applied to imbalanced dataset. In this paper we propose a maximum entropy machine (MEM) based hybrid algorithm to handle binary classification problems with high imbalance ratios and large numbers of features in the datasets. At the training stage, we combine an efficient MEM algorithm with the SMOTE algorithm to build a classifier in a batch manner. At the application stage, the different-cost strategy is incorporated into the MEM algorithm to handle the imbalance learning problem in an online manner. Experiments are conducted based on various real datasets (including one China Mobile dataset and several other standard test datasets) with different imbalance ratios and different numbers of features. The results show that the proposed algorithm outperforms the state-of-The-Art algorithms significantly in terms of robustness and overall classification performance.",

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note = "Funding Information: This work was supported by Shenzhen Fundamental Research Fund under Grant No. KQTD2015033114415450. The author Feng Yin was supported by Shenzhen Science and Technology Innovation Committee (KCW) project with Grant No. JCYJ20170307155957688 and NSFC with Grant No. 61701426. Feng Yin was funded by the Shenzhen Science and Technology Innovation Council with the grant number JCYJ20170307155957688 and JCYJ20170411102101881 and partly by the Shenzhen Fundamental Research Fund under Grant No. KQTD2015033114415450. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE/CIC International Conference on Communications in China, ICCC 2018 ; Conference date: 16-08-2018 Through 18-08-2018",

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Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Publisher link

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