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Training of ANFIS Network by Genetic Algorithm for Diagnosis of Leukemia Cancer Subtypes Using Gene Expression Profile
Date
2017-05-12
Author
Arslan, Mustafa Turan
Haznedar, Bülent
Kalınlı, Adem
Metadata
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In this study, subtypes of Leukemia cancer has classified by using microarray gene expression profiles. An approach is proposed to train Adaptive Neuro Fuzzy Inference System (ANFIS) network by using a population-based Genetic Algorithm (GA) to classify this cancer data. The classification success of the proposed model has compared with the successes of Backpropagation (BP)-ANFIS and Hybrid-ANFIS, which are derivative based ANFIS models. According to obtained results, GA-ANFIS model has performed very well on leukemia cancer, with 90.91% in the classification study. For the same data, BPANFIS and Hybrid-ANFIS models have performed poorly with 63.63% and 59.09%, respectively.
Subject Keywords
Microarray gene expression profile
,
ANFIS
,
Genetic Algorithm
,
Classification
URI
https://hdl.handle.net/11511/73791
https://www.icatsconf.org/uploads/files2/icat17-proceeding-v2-1.pdf
Conference Name
5th International Conference on Advanced Technology & Sciences (ICAT'17), (May 09-12)
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M. T. Arslan, B. Haznedar, and A. Kalınlı, “Training of ANFIS Network by Genetic Algorithm for Diagnosis of Leukemia Cancer Subtypes Using Gene Expression Profile,” İstanbul, Türkiye, 2017, p. 19, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73791.
