Markov blanket

A Markov blanket is a concept from probability theory and machine learning that identifies the smallest set of variables needed to predict a specific variable's behavior. Essentially, it includes all the direct causes, effects, and variables that influence or are influenced by the target variable. Knowing the Markov blanket allows you to make the best possible prediction about the target without needing information about the entire system. It helps in simplifying models and understanding relationships by focusing only on relevant variables for prediction or analysis.