Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses

Zeyneb Kurt; Oguzhan Yavuz

Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses

Zeyneb Kurt^*, Oguzhan Yavuz

^*Corresponding author for this work

School of Computer Science

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

Abstract

We propose intelligent methods to classify two different HIV virus types, i.e., R5X4 and R5 or X4 with low computational complexity. Since R5X5 virus has same the features of R5 and X4 viruses, diagnosis of R5X4 can not be determined easily. In this study, the statistical data of R5X4, R5 and X4 was obtained by accessible residues and modelled by Auto-regressive (AR) model. After that the pre-processed data was used for determining the optimal σ value in Radial Basis Kernel of Support Vector Machine (SVM).

Original language	English
Title of host publication	SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications
Pages	163-166
Number of pages	4
Publication status	Published - 2010
Event	International Conference on Signal Processing and Multimedia Applications, SIGMAP 2010 - Athens, Greece Duration: 26 Jul 2010 → 28 Jul 2010

Publication series

Name	SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications

Conference

Conference	International Conference on Signal Processing and Multimedia Applications, SIGMAP 2010
Country/Territory	Greece
City	Athens
Period	26/07/10 → 28/07/10

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Auto-regressive Model
HTV
ROC analysis
Support Vector Machine

Cite this

Kurt, Z., & Yavuz, O. (2010). Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses. In SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications (pp. 163-166). (SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications).

Kurt, Zeyneb ; Yavuz, Oguzhan. / Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses. SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications. 2010. pp. 163-166 (SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications).

@inproceedings{940ddde2a81f4313a27ed8c85a42b61d,

title = "Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses",

abstract = "We propose intelligent methods to classify two different HIV virus types, i.e., R5X4 and R5 or X4 with low computational complexity. Since R5X5 virus has same the features of R5 and X4 viruses, diagnosis of R5X4 can not be determined easily. In this study, the statistical data of R5X4, R5 and X4 was obtained by accessible residues and modelled by Auto-regressive (AR) model. After that the pre-processed data was used for determining the optimal σ value in Radial Basis Kernel of Support Vector Machine (SVM).",

keywords = "Auto-regressive Model, HTV, ROC analysis, Support Vector Machine",

author = "Zeyneb Kurt and Oguzhan Yavuz",

year = "2010",

language = "English",

isbn = "9789898425195",

series = "SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications",

pages = "163--166",

booktitle = "SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications",

note = "International Conference on Signal Processing and Multimedia Applications, SIGMAP 2010 ; Conference date: 26-07-2010 Through 28-07-2010",

}

Kurt, Z & Yavuz, O 2010, Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses. in SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications. SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications, pp. 163-166, International Conference on Signal Processing and Multimedia Applications, SIGMAP 2010, Athens, Greece, 26/07/10.

Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses. / Kurt, Zeyneb; Yavuz, Oguzhan.
SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications. 2010. p. 163-166 (SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications).

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

TY - GEN

T1 - Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses

AU - Kurt, Zeyneb

AU - Yavuz, Oguzhan

PY - 2010

Y1 - 2010

N2 - We propose intelligent methods to classify two different HIV virus types, i.e., R5X4 and R5 or X4 with low computational complexity. Since R5X5 virus has same the features of R5 and X4 viruses, diagnosis of R5X4 can not be determined easily. In this study, the statistical data of R5X4, R5 and X4 was obtained by accessible residues and modelled by Auto-regressive (AR) model. After that the pre-processed data was used for determining the optimal σ value in Radial Basis Kernel of Support Vector Machine (SVM).

AB - We propose intelligent methods to classify two different HIV virus types, i.e., R5X4 and R5 or X4 with low computational complexity. Since R5X5 virus has same the features of R5 and X4 viruses, diagnosis of R5X4 can not be determined easily. In this study, the statistical data of R5X4, R5 and X4 was obtained by accessible residues and modelled by Auto-regressive (AR) model. After that the pre-processed data was used for determining the optimal σ value in Radial Basis Kernel of Support Vector Machine (SVM).

KW - Auto-regressive Model

KW - HTV

KW - ROC analysis

KW - Support Vector Machine

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M3 - Conference contribution

AN - SCOPUS:78751542985

SN - 9789898425195

T3 - SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications

SP - 163

EP - 166

BT - SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications

T2 - International Conference on Signal Processing and Multimedia Applications, SIGMAP 2010

Y2 - 26 July 2010 through 28 July 2010

ER -

Kurt Z, Yavuz O. Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses. In SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications. 2010. p. 163-166. (SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications).

Searching optimal sigma parameter in Radial Basis Kernel Support Vector Machine for classification of HIV sub-type viruses

Abstract

Publication series

Conference

UN SDGs

Keywords

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Cite this