A New Procedure for Unsupervised Clustering Based on Combination of Artificial Neural Networks
Ярослава Миколаївна Пушкарьова, Paul Kholodniuk · European Journal of Artificial Intelligence and Machine Learning · 2023
Classification methods have become one of the main tools for extracting essential information from multivariate data. New classification algorithms are continuously being proposed and created. This paper presents a classification procedure based on a combination of Kohonen and probabilistic neural networks. Its applicability and efficiency are estimated using model data sets (iris flowers data set, wine data set, data with a two-hierarchical structure), then compared with the traditional clustering algorithms (hierarchical clustering, k-means clustering, fuzzy k-means clustering). The algorithm was designed as M-script in Matlab 7.11b software. It was shown that the proposed classification procedure has a great advantage over traditional clustering methods.