Segmentation of data samples in the analysis of the security state of internet of things devices.

The technique of segmenting data samples in order to improve the quality indicators of classifying algorithms is considered. It takes into account the factors that affect the change in the ranges of values of the target variables. Identifying impacts on current and anticipated situations makes it possible to segment data samples. As a result, the ranges of the studied variables and outliers are reduced, and noisy data are removed. The conducted experiment with the use of a divided sample is described. The evaluation results for each classifier on the total sample and on the segments are obtained. [ABSTRACT FROM AUTHOR]