Do-calculus is a formal framework developed to reason about causal effects and interventions in statistical models. It provides rules and methods to manipulate causal expressions involving interventions, helping to identify and estimate causal relationships. This tool is essential for understanding counterfactuals, designing interventions, and applying causal inference techniques across various fields, including machine learning.
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