Cause Effect Pairs In Machine Learning - Springer Nature B.V

This Book Presents Ground-breaking Advances In The Domain Of Causal Structure Learning.the Problem Of Distinguishing Cause From Effect( Does Altitude Cause A Change In Atmospheric Pressure, Or Vice Versa? ) Is Here Cast As A Binary Classification Problem, To Be Tackled By Machine Learning Algorithms. Based On The Results Of Thechalearn Cause-effect Pairs Challenge, This Book Reveals That The Joint Distribution Of Two Variables Can Be Scrutinized By Machine Learning Algorithms To Reveal The Possible Existence Of A Causal Mechanism, In The Sense That The Values Of One Variable May Have Been Generated From The Values Of The Other.this Book Provides Both Tutorial Material On The State-of-the-art On Cause-effect Pairs And Exposes The Reader To More Advanced Material, With A Collection Of Selected Papers.