Single Parent Networks

Single Parent Networks are a type of probabilistic model used to understand complex relationships between variables, where each variable depends on only one other variable. In these networks, nodes represent variables, and edges show direct dependencies. This structure simplifies calculations and inference, making it easier to analyze how changes in one variable can affect others. Single Parent Networks are useful in fields like machine learning and diagnostics, providing a clear framework to model systems with hierarchical or dependent relationships without excessive computational complexity.