ITM Web Conf.
Volume 59, 2024II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
|Number of page(s)
|Data Mining, Machine Learning and Patern Recognition
|25 January 2024
Influence of the number of attribute binarization thresholds on the quality of the generated set of rules for the method of logical analysis of data
Siberian Federal University,
79, Svobodny Ave.,
* Corresponding author: firstname.lastname@example.org
For efficient operation of machine learning methods, it is necessary to set their parameters up properly. Both the computational complexity and the accuracy of the method for the problem being solved can depend on the selected parameter values. The paper discusses the method of logical analysis of data, which is used to solve classification problems and consists of a number of steps. At each step, it is necessary to set the method parameters up to suit the problem being solved. When setting parameters, one should be guided by a compromise between the accuracy of the method and the computational complexity. With comparable values for classification accuracy of several variants of the method implementation, preference will always be given to the simplest of them in terms of computational complexity. Since the method works only with binary characteristics, at the first stage it is necessary to binarize quantitative characteristics. The binarization procedure is associated with the choice of the “number of binarization thresholds” parameter. This paper proposes an experimental approach to determine the best value of the specified method parameter for the problem being solved.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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