Greedy Heuristics for the Choice of the Radius of Local Concentrations in FOREL-2 Algorithm
Abstract
The authors examine the problem of choosing the search radius for local concentrations in the FOREL-2 clustering algorithm with an initial number of clusters. Our approach was aimed at improving the accuracy and stability of the result, such as identifying homogeneous batches of industrial products. We examined the k-means and FOREL-2 algorithms by using normalized standard deviation test values and by valid parameter values for the problem of automatic classification of objects in a multi-dimensional space of measured parameters. For such problems, with the use of the FOREL-2 algorithm, we apply greedy heuristic procedures to select the radius of local concentrations. According to the obtained Rand index, the approach which uses the FOREL-2 algorithm demonstrated the best accuracy with a larger value of the objective function in comparison with the k-means algorithm. The accuracy and speed of the software implementation of the algorithm are quite acceptable for solving the problem of clustering electronic radio products based on test data. The use of greedy heuristics for choosing the radius of the search for local concentrations in the FOREL-2 clustering algorithm with a specified number of clusters has an advantage in the speed of exact clustering compared to the k-means algorithm that uses greedy heuristics for choosing centroids.
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About this article
Publication Date
27 February 2023
Article Doi
eBook ISBN
978-1-80296-960-3
Publisher
European Publisher
Volume
1
Print ISBN (optional)
-
Edition Number
1st Edition
Pages
1-403
Subjects
Hybrid methods, modeling and optimization, complex systems, mathematical models, data mining, computational intelligence
Cite this article as:
Ahmatshin, F. G., & Kazakovtsev, L. A. (2023). Greedy Heuristics for the Choice of the Radius of Local Concentrations in FOREL-2 Algorithm. In P. Stanimorovic, A. A. Stupina, E. Semenkin, & I. V. Kovalev (Eds.), Hybrid Methods of Modeling and Optimization in Complex Systems, vol 1. European Proceedings of Computers and Technology (pp. 366-371). European Publisher. https://doi.org/10.15405/epct.23021.45