Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization

Kemal Adem

doi:10.29137/umagd.472881

EN

Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization

Abstract

Late diagnosis of chronic kidney disease, a disease that has increased in recent years and threatens human life, may lead to dialysis or kidney failure. In this study, kNN, SVM, RBF and Random subspace data mining methods were applied on the data set consisting of 400 samples and 24 attributes taken from UCI for classification of chronic kidney disease with particle swarm optimization (PSO) based feature selection method. As a result of the study, the results of the application of each data mining method are compared with the resultant training and test results. As a result of the comparison, it was seen that the method of PSO feature selection affects the classification success positively. Moreover, as a method of data mining, it has been seen that the random subspace method has higher accuracy rates than the other methods.

Keywords

Chronic kidney disease,Particle Swarm Optimization,Random Subspace

References

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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Kemal Adem
0000-0002-3752-7354
Türkiye

Publication Date

December 31, 2018

Submission Date

October 21, 2018

Acceptance Date

December 12, 2018

Published in Issue

Year 2018 Volume: 10 Number: 3

DOI

https://doi.org/10.29137/umagd.472881

IZ

https://izlik.org/JA74JR48XM

APA

Adem, K. (2018). Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization. International Journal of Engineering Research and Development, 10(3), 1-5. https://doi.org/10.29137/umagd.472881

AMA

1.Adem K. Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization. IJERAD. 2018;10(3):1-5. doi:10.29137/umagd.472881

Chicago

Adem, Kemal. 2018. “Diagnosis of Chronic Kidney Disease Using Random Subspace Method With Particle Swarm Optimization”. International Journal of Engineering Research and Development 10 (3): 1-5. https://doi.org/10.29137/umagd.472881.

EndNote

Adem K (December 1, 2018) Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization. International Journal of Engineering Research and Development 10 3 1–5.

IEEE

[1]K. Adem, “Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization”, IJERAD, vol. 10, no. 3, pp. 1–5, Dec. 2018, doi: 10.29137/umagd.472881.

ISNAD

Adem, Kemal. “Diagnosis of Chronic Kidney Disease Using Random Subspace Method With Particle Swarm Optimization”. International Journal of Engineering Research and Development 10/3 (December 1, 2018): 1-5. https://doi.org/10.29137/umagd.472881.

JAMA

1.Adem K. Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization. IJERAD. 2018;10:1–5.

MLA

Adem, Kemal. “Diagnosis of Chronic Kidney Disease Using Random Subspace Method With Particle Swarm Optimization”. International Journal of Engineering Research and Development, vol. 10, no. 3, Dec. 2018, pp. 1-5, doi:10.29137/umagd.472881.

Vancouver

1.Kemal Adem. Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization. IJERAD. 2018 Dec. 1;10(3):1-5. doi:10.29137/umagd.472881

Kırıkkale University, Faculty of Engineering and Natural Science, 71450 Yahşihan / Kırıkkale, Türkiye.

ijerad@kku.edu.tr

Abstract

Diagnosis of Chronic Kidney Disease using Random Subspace Method with Particle Swarm Optimization

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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