Cause Effect Pairs in Machine Learning

• Corporate Author: SpringerLink (Online service)
• Other Authors: Guyon, Isabelle (Editor, http://id.loc.gov/vocabulary/relators/edt), Statnikov, Alexander (Editor, http://id.loc.gov/vocabulary/relators/edt), Batu, Berna Bakir (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: The Springer Series on Challenges in Machine Learning,
• Subjects: Artificial intelligence.; Optical data processing.; Pattern recognition.; Artificial Intelligence.; Image Processing and Computer Vision.; Pattern Recognition.

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 learnin...