Structure Learning

Structure learning is a process used in data analysis to discover how different variables are connected or related, often represented as a network or graph. It involves identifying which variables influence each other and how, helping to understand the underlying system or pattern. This is useful in fields like medicine, finance, or machine learning, where understanding these relationships improves predictions and decisions. Essentially, structure learning uncovers the blueprint of connections within complex data sets to reveal the underlying structure driving observed behaviors or outcomes.