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CausalX: Causal Explanations and Block Multilinear Factor Analysis
[article]
2021
arXiv
pre-print
By adhering to the dictum, "No causation without manipulation (treatment, intervention)", cause and effect data analysis represents changes in observed data in terms of changes in the causal factors. When causal factors are not amenable for active manipulation in the real world due to current technological limitations or ethical considerations, a counterfactual approach performs an intervention on the model of data formation. In the case of object representation or activity (temporal object)
arXiv:2102.12853v2
fatcat:3dizqcutdjfq5dubsodqja2h7e