An Ensemble Classifier Method for Breast Cancer Detection Using Genetic Algorithm and Multistage Adjustment of Weights in the MLP Neural Network

Message:
Article Type:
Research/Original Article (بدون رتبه معتبر)
Abstract:

Today, with the increasing spread of science, the use of decision support systems can be of great help in the therapeutic policies of the Doctor. For this purpose, the use of artificial intelligence systems in predicting and diagnosing breast cancer, which is one of the most common cancers among women, is being considered. In this study, the process of diagnosis of breast cancer is done by using multistage weights in the MLP neural network in two layers. In the first layer, the three classifiers are trained simultaneously on the learning set data. Upon completion of the training, the output of the classifier of the first layer is accumulated together with the learning set data in the new sets. This set is given as an input to the second layer superconductor, and the supra-class mapping maps between the outputs of each of the ordinary classifiers of the first layer with the actual output classes. The three-layer structure of the first layer, as well as the second-layer supraclavicle, is a MLP neural network that optimizes the weights, effective properties and the size of the hidden layer simultaneously using an innovative genetic algorithm. In order to evaluate the accuracy of the proposed model, the Wisconsin database is used, which was created by the FNA test. Experiment results on the WBCD dataset the accuracy is 98.72% for the proposed method, which is relative to GAANN, CAFS algorithms provide better performance.

Language:
Persian
Published:
Journal of Southern Communication Engineering, Volume:10 Issue: 40, 2021
Pages:
1 to 16
https://www.magiran.com/p2417703  
سامانه نویسندگان
  • Amin Rezaeipanah
    Corresponding Author (1)
    Instructor University of Rahjuyan Danesh Borazjan, Rahjoyan Dabesh Institute of Higher Education, Borazjan, Iran
    Rezaeipanah، Amin
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