АУЫЛШАРУАШЫЛЫҚ РЕСУРСТАРЫН БАСҚАРУДЫ ОҢТАЙЛАНДЫРУ ҮШІН SHAP ЖӘНЕ PCA ҚОЛДАНУ АРҚЫЛЫ ФАКТОРЛАРДЫҢ МАҢЫЗДЫЛЫҒЫН ТАЛДАУ

Abstract

The article presents a comprehensive approach to analyzing the significance of factors in the agro-industrial sector. This approach employs methods such as SHAP (Shapley Additive Explanations), Simple Combination, and PCA (Principal Component Analysis) + Combination. The study addresses the necessity of efficiently managing agricultural resources under limited and changing climatic conditions. The proposed methodology evaluates the impact of various factors on key indicators such as productivity, income, and operational costs. SHAP analysis identified the main determining factors, showing that "Land area (ha)" significantly affects "Market capacity" (59.5%) and "Sales income" (57.2%), highlighting the importance of production scale. The Simple Combination method (combining Gradient Boosting, Mutual Information, and RFE + Lasso) identified a balanced distribution of factors: "Land area" – 14.5%, "Seed usage" – 12.8%, "Fertilizer expenses" – 10.7%. The PCA + Combination method revealed global trends, identifying "Yield per hectare" (22.5%) and "Crop area size" (11.5%) as the primary factors driving major changes. This integrated approach enables a deep analysis of data, covering both local effects and global interdependencies. The obtained results are crucial for optimal resource management, strategic planning, and enhancing agricultural production efficiency