In this paper we derive variability measures for the conditional probability distributions of a pair of random variables, and we study its application in the inference of causal-effect relationships. We also study the combination of the proposed measures with standard statistical measures in the the framework of the ChaLearn cause-effect pair challenge. The developed model obtains an AUC score of 0.82 on the final test database and ranked second in the challenge.
CITATION STYLE
Fonollosa, J. A. R. (2019). Conditional Distribution Variability Measures for Causality Detection (pp. 339–347). https://doi.org/10.1007/978-3-030-21810-2_12
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