why causal discovery?
Beyond Correlation
Beyond correlation refers to methods and principles that move past simple statistical associations to uncover true causal relationships between variables.Correlation alone does not imply causation, as two variables may be correlated due to confounding factors,reverse causation, or mere coincidence.
Decision Optimization
Decision optimization in causal discovery refers to the process of selecting the best causal model or intervention strategy to maximize desired outcomes based on inferred causal relationships. This involves both identifying the true causal structure from data and optimizing decisions based on the discovered causal relationships.
Counterfactual Reasoning
Counterfactual reasoning is a core concept in causal inference, where we ask"what if?" questions to determine how outcomes would change if a different decision, action, or event had occurred.It helps in understanding causality beyond mere correlation by evaluating alternative realities.