Metrics on Markov Equivalence Classes for Evaluating Causal Discovery
Algorithms
Metrics on Markov Equivalence Classes for Evaluating Causal Discovery
Algorithms
Many state-of-the-art causal discovery methods aim to generate an output graph that encodes the graphical separation and connection statements of the causal graph that underlies the data-generating process. In this work, we argue that an evaluation of a causal discovery method against synthetic data should include an analysis of how …