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Dominik Janzing - Submitted: 2010-05-04 13:53 - Views : 2279 -
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- Authors: Joris Mooij, Dominik Janzing, Bernhard Schölkopf
- Key facts: The goal of this task is to distinguish between cause and effect.
Detailed description
For a given N x 2 matrix (containing N samples of 2 continuous variables) where one variable is known to causally influence the other, but not vice versa, the task is to identify which variable is the cause and which one the effect.
Data origin
For this task, the origin of the data is hidden for the participants but known to the organizers. The data sets are chosen such that we expect common agreement on which one is the cause and which one the effect. Even though part of the statistical dependences may also be due to hidden common causes, common sense tells us that there is a significant cause-effect-relation.
- Keywords: pairwise causal inference
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Abstract:
The data set consists of 8 N x 2 matrices, each representing a cause-effect pair and the task is to identify which variable is the cause and which one the effect.
The origin of the data is hidden for the participants but known to the organizers. The data sets are chosen such that we expect common agreement on which one is the cause and which one the effect. Even though part of the statistical dependences may also be due to hidden common causes, common sense tells us that there is a significant cause-effect-relation.
