A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis

Meir Perez; David M. Rubin; Lesley E. Scott; Tshilidzi Marwala; Wendy Stevens

doi:10.1109/EEEI.2008.4736603

A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis

Meir Perez
, David M. Rubin
, Lesley E. Scott
, Tshilidzi Marwala
, Wendy Stevens

University of the Witwatersrand

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

13 Citations (Scopus)

Abstract

A Hybrid Fuzzy-SVM classifier, used to automate leukaemia diagnosis based on microarray gene expression data, is presented. A publically available dataset was used to develop and test the classifier. A Fuzzy Gene Filter was developed to select the genes which show significant class variation between various leukaemia types. The results obtained from using all the genes for classification is compared to those obtained when only the top 25 differentiating genes are used. The filtered gene classifier was able to correctly classify the entire test dataset, compared to the unfiltered gene classifier which was only able to achieve an accuracy of 84.2%. The results show that, by reducing dimensionality, classification accuracy is improved since redundant information is excluded, thereby limiting the effect of potential outliers.

Original language	English
Title of host publication	2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
Pages	41-45
Number of pages	5
DOIs	https://doi.org/10.1109/EEEI.2008.4736603
Publication status	Published - 2008
Externally published	Yes
Event	2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008 - Eilat, Israel Duration: 3 Dec 2008 → 5 Dec 2008

Publication series

Name	IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings

Conference

Conference	2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
Country/Territory	Israel
City	Eilat
Period	3/12/08 → 5/12/08

UN SDGs

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

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/EEEI.2008.4736603

Cite this

Perez, M., Rubin, D. M., Scott, L. E., Marwala, T., & Stevens, W. (2008). A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis. In 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008 (pp. 41-45). Article 4736603 (IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings). https://doi.org/10.1109/EEEI.2008.4736603

@inproceedings{de53e8fcc009465fa2a600a67ff911fa,

title = "A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis",

abstract = "A Hybrid Fuzzy-SVM classifier, used to automate leukaemia diagnosis based on microarray gene expression data, is presented. A publically available dataset was used to develop and test the classifier. A Fuzzy Gene Filter was developed to select the genes which show significant class variation between various leukaemia types. The results obtained from using all the genes for classification is compared to those obtained when only the top 25 differentiating genes are used. The filtered gene classifier was able to correctly classify the entire test dataset, compared to the unfiltered gene classifier which was only able to achieve an accuracy of 84.2\%. The results show that, by reducing dimensionality, classification accuracy is improved since redundant information is excluded, thereby limiting the effect of potential outliers.",

author = "Meir Perez and Rubin, \{David M.\} and Scott, \{Lesley E.\} and Tshilidzi Marwala and Wendy Stevens",

year = "2008",

doi = "10.1109/EEEI.2008.4736603",

language = "English",

isbn = "9781424424825",

series = "IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings",

pages = "41--45",

booktitle = "2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008",

note = "2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008 ; Conference date: 03-12-2008 Through 05-12-2008",

}

Perez, M, Rubin, DM, Scott, LE, Marwala, T & Stevens, W 2008, A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis. in 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008., 4736603, IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings, pp. 41-45, 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008, Eilat, Israel, 3/12/08. https://doi.org/10.1109/EEEI.2008.4736603

A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis. / Perez, Meir; Rubin, David M.; Scott, Lesley E. et al.
2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008. 2008. p. 41-45 4736603 (IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings).

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

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AU - Stevens, Wendy

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AB - A Hybrid Fuzzy-SVM classifier, used to automate leukaemia diagnosis based on microarray gene expression data, is presented. A publically available dataset was used to develop and test the classifier. A Fuzzy Gene Filter was developed to select the genes which show significant class variation between various leukaemia types. The results obtained from using all the genes for classification is compared to those obtained when only the top 25 differentiating genes are used. The filtered gene classifier was able to correctly classify the entire test dataset, compared to the unfiltered gene classifier which was only able to achieve an accuracy of 84.2%. The results show that, by reducing dimensionality, classification accuracy is improved since redundant information is excluded, thereby limiting the effect of potential outliers.

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M3 - Conference contribution

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ER -

Perez M, Rubin DM, Scott LE, Marwala T, Stevens W. A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis. In 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008. 2008. p. 41-45. 4736603. (IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings). doi: 10.1109/EEEI.2008.4736603

A Hybrid Fuzzy-SVM classifier, applied to gene expression profiling for automated leukaemia diagnosis

Abstract

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UN SDGs

ASJC Scopus subject areas

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