A Review on Algorithms for Constraint-based Causal Discovery

Understand

Causal discovery studies the problem of mining causal relationships between variables from data, which is of primary interest in science.

• During the past decades, significant amount of progresses have been made toward this fundamental data mining paradigm.
• Recent years, as the availability of abundant large-sized and complex observational data, the constrain-based approaches have gradually attracted a lot of interest and have been widely applied to many diverse real-world problems due to the fast running speed and easy generalizing to the problem of causal insufficiency.
• In this paper, we aim to review the constraint-based causal discovery algorithms.