Open AccessONLINE MODIFICATION OF THE METHOD OF X-MEDIUM ON THE BASIS OF ANSAMBLY OF SELORGANIZED MAP T. KOHONEN
Author(s) -
Є. В. Бодянський,
Anastasiia Deineko,
Polina Zhernova,
Vladyslav O. Riepin
Publication year - 2017
Publication title -
rozvitok transportu
Language(s) - English
Resource type - Journals
ISSN - 2616-7360
DOI - 10.33082/td.2017.1-1.10
Subject(s) - self organizing map , cluster analysis , computer science , artificial neural network , pattern recognition (psychology) , artificial intelligence , data mining , similarity (geometry) , basis (linear algebra) , process (computing) , measure (data warehouse) , feature (linguistics) , mathematics , image (mathematics) , linguistics , philosophy , geometry , operating system
The modified X-means method for clustering in the case when observations are sequentially fed to processing the proposed. This approach’s based on the ensemble of the clustering neural networks, proposed ensemble contains the T. Kohonen’s self-organizing maps. Each of the clustering neural networks consist of different number of neurons, where number of clusters is connected with the quality of there neurons. All ensemble members process information that siquentionally is fed to the system in the parallel mode. The effectiveness of clustering process is determined using Caliński-Harabasz index. The self-learning algorithm uses similarity measure of special type that. The feature of proposed method is absent of the competition step, i.e. neuron-winner is not determined. A number of experiments has been held in order to investigate the proposed system’s properties. Experimental results have proven the fact that the system under consideration could be used to solve a wide range of Data Mining tasks when data sets are processed in an online mode. The proposed ensemble system provides computational simplicity, and data sets are pro-cessed faster due to the possibility of parallel tuning.