Effective cancer classification based on gene expression data using multidimensional mutual information and ELM

Qun Xiong Zhu; Yuan Fan; Yan Lin He; Yuan Xu

doi:10.1109/DDCLS.2018.8515927

Effective cancer classification based on gene expression data using multidimensional mutual information and ELM

Qun Xiong Zhu, Yuan Fan, Yan Lin He, Yuan Xu

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

3 Citations (Scopus)

Abstract

In the field of microarray data research, it is quite challenging to make classification due to small sample size and the high dimension of data. Moreover, the feature selection is crucial. In this paper, we propose multidimensional mutual information (MMI) feature selection method to select the most informative features for classification. After feature selection using the proposed MMI, Extreme Learning Machine (ELM) is used as an efficient classifier. So as to evaluate the performance of the proposed methodology, a typical dataset called Leukemia is selected to carry out a case study. Simulation results demonstrate the effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	954-958
Number of pages	5
ISBN (Electronic)	9781538626184
DOIs	https://doi.org/10.1109/DDCLS.2018.8515927
Publication status	Published - 30 Oct 2018
Externally published	Yes
Event	7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018 - Enshi, Hubei Province, China Duration: 25 May 2018 → 27 May 2018

Publication series

Name	Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018

Conference

Conference	7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018
Country/Territory	China
City	Enshi, Hubei Province
Period	25/05/18 → 27/05/18

Keywords

classification
extreme machine learning
feature selection
Gene expression data
information gain

UN SDGs

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

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10.1109/DDCLS.2018.8515927

Cite this

Zhu, Q. X., Fan, Y., He, Y. L., & Xu, Y. (2018). Effective cancer classification based on gene expression data using multidimensional mutual information and ELM. In Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018 (pp. 954-958). Article 8515927 (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DDCLS.2018.8515927

Zhu, Qun Xiong ; Fan, Yuan ; He, Yan Lin et al. / Effective cancer classification based on gene expression data using multidimensional mutual information and ELM. Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 954-958 (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018).

@inproceedings{2ddcc5844b7b499cb0668366fed4a6ff,

title = "Effective cancer classification based on gene expression data using multidimensional mutual information and ELM",

abstract = "In the field of microarray data research, it is quite challenging to make classification due to small sample size and the high dimension of data. Moreover, the feature selection is crucial. In this paper, we propose multidimensional mutual information (MMI) feature selection method to select the most informative features for classification. After feature selection using the proposed MMI, Extreme Learning Machine (ELM) is used as an efficient classifier. So as to evaluate the performance of the proposed methodology, a typical dataset called Leukemia is selected to carry out a case study. Simulation results demonstrate the effectiveness of the proposed method.",

keywords = "classification, extreme machine learning, feature selection, Gene expression data, information gain",

author = "Zhu, {Qun Xiong} and Yuan Fan and He, {Yan Lin} and Yuan Xu",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018 ; Conference date: 25-05-2018 Through 27-05-2018",

year = "2018",

month = oct,

day = "30",

doi = "10.1109/DDCLS.2018.8515927",

language = "English",

series = "Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "954--958",

booktitle = "Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018",

address = "United States",

}

Zhu, QX, Fan, Y, He, YL & Xu, Y 2018, Effective cancer classification based on gene expression data using multidimensional mutual information and ELM. in Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018., 8515927, Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 954-958, 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018, Enshi, Hubei Province, China, 25/05/18. https://doi.org/10.1109/DDCLS.2018.8515927

Effective cancer classification based on gene expression data using multidimensional mutual information and ELM. / Zhu, Qun Xiong; Fan, Yuan; He, Yan Lin et al.
Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 954-958 8515927 (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018).

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

TY - GEN

T1 - Effective cancer classification based on gene expression data using multidimensional mutual information and ELM

AU - Zhu, Qun Xiong

AU - Fan, Yuan

AU - He, Yan Lin

AU - Xu, Yuan

PY - 2018/10/30

Y1 - 2018/10/30

N2 - In the field of microarray data research, it is quite challenging to make classification due to small sample size and the high dimension of data. Moreover, the feature selection is crucial. In this paper, we propose multidimensional mutual information (MMI) feature selection method to select the most informative features for classification. After feature selection using the proposed MMI, Extreme Learning Machine (ELM) is used as an efficient classifier. So as to evaluate the performance of the proposed methodology, a typical dataset called Leukemia is selected to carry out a case study. Simulation results demonstrate the effectiveness of the proposed method.

AB - In the field of microarray data research, it is quite challenging to make classification due to small sample size and the high dimension of data. Moreover, the feature selection is crucial. In this paper, we propose multidimensional mutual information (MMI) feature selection method to select the most informative features for classification. After feature selection using the proposed MMI, Extreme Learning Machine (ELM) is used as an efficient classifier. So as to evaluate the performance of the proposed methodology, a typical dataset called Leukemia is selected to carry out a case study. Simulation results demonstrate the effectiveness of the proposed method.

KW - classification

KW - extreme machine learning

KW - feature selection

KW - Gene expression data

KW - information gain

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U2 - 10.1109/DDCLS.2018.8515927

DO - 10.1109/DDCLS.2018.8515927

M3 - Conference contribution

AN - SCOPUS:85057011564

T3 - Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018

SP - 954

EP - 958

BT - Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018

Y2 - 25 May 2018 through 27 May 2018

ER -

Zhu QX, Fan Y, He YL, Xu Y. Effective cancer classification based on gene expression data using multidimensional mutual information and ELM. In Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 954-958. 8515927. (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018). doi: 10.1109/DDCLS.2018.8515927

Effective cancer classification based on gene expression data using multidimensional mutual information and ELM

Abstract

Publication series

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Keywords

UN SDGs

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