# The Use of Machine Learning for Comparative Analysis of
###### Abstract  
This paper presents an analysis of modern methods used to determine antioxidant activity. According to research by the World Health Organization, the deficiency of such important nutrients as antioxidants leads to a decrease in body resistance and the development of chronic diseases. When it comes to diet, the inclusion of foods with a high content of antioxidants helps to increase life expectancy. As a result of this research, the mass concentration of phenolic substances and the antioxidant activity of phenolic antioxidants in young white and red table wine materials were determined using amperometric and chemiluminescent methods in order to determine antioxidant activity. Regression equations reflecting the relationship between the indicator of antioxidant activity and the value of the mass concentration of phenolic substances in young table wine materials were derived. The conversion coefficient for determining the mass concentration of phenolic substances when using Trolox-C and gallic acid as standards was established, which was--3.75. Based on a multiple linear regression model, the total antioxidant activity of the samples (F\({}_{9.5}\) = 19.10 and \(p\) = 0.0023) can be fairly accurately predicted with an R\({}^{2}\) of 0.921 for the calibration data set. A neural network regression model (NNRM) was chosen for the machine-learning regression analysis of the antioxidant activity of the wine samples due to its effectiveness in predicting outcomes in various applications. The implementation was performed using the firmet function provided in the Statistics and Machine Learning Toolbox in MATLAB R2021b. The MSE of the calibration model was 0.056; however, the MSE for the three validation samples was much higher, at 0.272. An actioxidant activity; amperometric method; chemiluminescent method; phenolic substances; machine learning +
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mass (uTE/100 g). An insufficient number of antioxidants in the body increases the risk of the onset and progression of cardiovascular and oncological diseases. To improve health, it is advisable to use food products enriched with biologically active substances, which include antioxidants. The experience of introducing a healthy eating program in Japan has shown its effectiveness and helped to increase life expectancy in the country by 8 years. Long-term studies of the antioxidant activity of vitamins, bioflavonoids, and enzymes, conducted by [PERSON] [PERSON] of the University of Nebraska, led to the creation of the \"Free Radical Theory of Aging\" in 1956 [1]. In the same year, Soviet academician [PERSON] received the Nobel Prize for the discovery of free radicals. The theory of [PERSON]. [PERSON] boils down to the fact that in the human body, under the influence of adverse environmental factors (solar radiation, stress, etc. ), free radicals are formed that negatively affect the cell organoids (mitochondria), and can also cause DNA mutations and oncological diseases. The natural obstacle to the formation of free radicals is the antioxidant system of the human body. The antioxidant substances included in them interact with free radicals and exhibit the properties of electron donors, thereby preventing the oxidation process [2; 3]. Recently, numerous studies have been conducted that confirm the high biological value and antioxidant activity of grape wines and other functional food products based on a more complete use of all of the components of grapes and bunches [4; 5; 6; 7; 8] and methods for determining their antioxidant activity have been developed. However, among the many developed methods, it is difficult to choose the most informative and accessible to use [9; 10; 11]. It is possible to distinguish groups of methods for determining AOA: titrimetric (in particular, coulometric, voltammetric, potentiometric, polarography); chromatographic (thin-layer chromatography, high-performance liquid chromatography); and spectral (spectrophotometry, TAC, TAEC, TBARP, DPPH, FRAP, CUPRAC, ABTS).