Is Information Theory Inherently a Theory of Causation?
Machine Learning
2020-11-10 v4 Information Theory
Machine Learning
math.IT
Abstract
Information theory gives rise to a novel method for causal skeleton discovery by expressing associations between variables as tensors. This tensor-based approach reduces the dimensionality of the data needed to test for conditional independence, e.g., for systems comprising three variables, the causal skeleton can be determined using pair-wise determined tensors. To arrive at this result, an additional information measure, path information, is proposed.
Keywords
Cite
@article{arxiv.2010.01932,
title = {Is Information Theory Inherently a Theory of Causation?},
author = {David Sigtermans},
journal= {arXiv preprint arXiv:2010.01932},
year = {2020}
}
Comments
4 pages, 1 figure