ITM Web Conf.
Volume 21, 2018Computing in Science and Technology (CST 2018)
|Number of page(s)||10|
|Published online||12 October 2018|
Clustering qualitative data based on the flow networks
Department of Applied Informatics, University of Information Technology and Management, Sucharskiego str. 2, 35-225 Rzeszow, Poland
2 Department of Computer Science, University of Rzeszow, Rejtana str. 16c, 35-225 Rzeszow, Poland
* Corresponding author: firstname.lastname@example.org
The paper presents research results referring to the use of flow networks and ant colony algorithm in the problem of generating decision rules for the cluster analysis process. The experiments showed that proposed approach may prove particularly important, when we are dealing with data sets represented by categorical variables associated with the same number of objects for each variance. There are many cases when we have no knowledge about the allocation group of individual data received and in addition defining any metric to measure the distance between observations, does not give any satisfactory results. Meanwhile, the selection of features and the choice of the performance metric is the basic condition for the use of most known classifiers. The article presents a new approach to solve this problem and obtain satisfactory results. It is based on mapping the set of analyzed data into the flow network, calculating the maximum flow and determining the validity of nodes in the network to use the Ant Colony Algorithm to structuring information and determine significant relationships between data.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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