Correlation does not imply Causality. Pearl's work shows that it is sometimes possible to reason and make inferences about causal relationships in data even wh

Correlation does not imply Causality. Pearl's work shows that it is sometimes possible to reason and make inferences about causal relationships in data even when a controlled experiment is not possible and sometimes not. Machine learning algorithms that differentiate between known causal relations from correlative relations should perform better. The amazing thing is how good an approximation to causality correlation may be. Interested in persuing this further? See http://www.michaelnielsen.org/ddi/if-correlation-doesnt-imply-causation-then-what-does/ http://www.michaelnielsen.org/ddi/if-correlation-doesnt-impl... and, I suppose, read Pearl's latest book.