Family pooling

Family pooling is a method used in data analysis and machine learning where information from multiple related individuals, like members of a family, is combined to improve accuracy and insights. Instead of analyzing each person separately, data from family members is aggregated, considering their genetic, environmental, or behavioral connections. This approach helps identify patterns or risks that may not be apparent in individual data alone, ultimately leading to better predictions or understanding of inherited traits, health outcomes, or shared influences within families.