Machine Learning Analysis of Key Features in Household Financial Decision-Making

This paper explores the potential and challenges of mobile Internet in household investment decisions. The rapid development of mobile Internet has brought opportunities and challenges to household asset allocation, especially in promoting greater participation in venture asset investment. This paper focuses on the application potential of machine learning in analyzing household investment behavior patterns and trends. It reveals the potential household income rules, consumption patterns and asset allocation preferences through extensive data analysis. However, machine learning faces many challenges, such as data privacy protection, algorithmic interpretation, and data acquisition costs. Finally, the paper calls for further research and exploration to deepen understanding of how technological innovation can drive intelligent and optimized household financial decisions.