MACHINE LEARNING-BASED ASSESSMENT AND FORECASTING OF REGIONAL FOOD INDUSTRY DEVELOPMENT: A CASE STUDY OF KASHKADARYA REGION

This article investigates the modeling of food manufacturing industry development using machine learning algorithms, with Kashkadarya Region as a case study. Economic, investment, technological, and production-related factors influencing the industry's innovative development are systematized, with particular attention to assessing their relationships with the outcome indicator. The study envisages the application of statistical analysis, data preprocessing, machine learning, and comparative evaluation. The potential of machine learning algorithms to identify complex nonlinear relationships, assess the relative importance of factors, and select a model with high predictive accuracy is examined.