A Primer on Causal Analysis
Machine Learning
2018-06-06 v1 Artificial Intelligence
Machine Learning
Abstract
We provide a conceptual map to navigate causal analysis problems. Focusing on the case of discrete random variables, we consider the case of causal effect estimation from observational data. The presented approaches apply also to continuous variables, but the issue of estimation becomes more complex. We then introduce the four schools of thought for causal analysis
Keywords
Cite
@article{arxiv.1806.01488,
title = {A Primer on Causal Analysis},
author = {Finnian Lattimore and Cheng Soon Ong},
journal= {arXiv preprint arXiv:1806.01488},
year = {2018}
}
Comments
Parts of this document are copied verbatim from Finnian Lattimore's PhD thesis, ANU 2018