Work

Karaciğer Mikroarray Kanser Verisinin Sınıflandırılması için Genetik Algoritma Kullanarak ANFIS’in eğitilmesi

Year: 2017

Type: article

Abstract: Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA) are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

Source: Sakarya University Journal of Science

DOI: 10.16984/saufenbilder.283823

Authors: Bülent Haznedar, Mustafa Turan Arslan, Adem Kalınlı

Institutions: Hasan Kalyoncu University, Gaziantep University, Mustafa Kemal University, Erciyes University

Language: Turkish

Topic: Gene expression and cancer classification

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: diamond

Funder: Erciyes Üniversitesi