Comparative Analysis of Artificial Neural Network Training Algorithms
Charos KhidirovaDepartment of Information Systems Software, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Uzbekistan
2020 International Conference on Information Science and Communications Technologies (ICISCT)conference2020en
ABI
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This study compares training algorithms for artificial neural networks such as genetic, adaptive and hybrid. The “Fisher's Irises” were used as a data for the classification problem and KNIME Analytics Platform was chosen as the experimental environment. Given results comparison analysis of three methods training for neural networks and their parameters are presented. The choice of the optimal architecture was carried out on the basis of the classification algorithm, based on the graph of classification accuracy and error.
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