Analysis of Elderly Care Services Based on Machine Learning and Factor Rotation Method

As China's aging population continues to escalate, the societal burden of elderly care has notably intensified. Presently, the spectrum of elderly care services in China encompasses institutional, community-based, and home-based care. Given the diverse needs of the elderly population, this study proposes an Elderly Care Service Selection Predictive Model. It aims to forecast the probable choice of elderly care service types by analyzing various characteristics of the elderly individuals. Simultaneously, considering the status of institutional versus community-based elderly care across different provinces and municipalities, alongside the basic demographics of the elderly, this research scrutinizes the supply and demand scenario of elderly care services in each region, assessing the equilibrium between the two. By forecasting elderly care service preferences and evaluating supply-demand dynamics, this analysis contributes to aiding governmental agencies in more rationally allocating elderly care resources across regions, thus meeting the diverse needs of the aging population.