Towards Automated Causal Discovery: a case study on 5G telecommunication
  data
Konstantina Biza Antonios Ntroumpogiannis Sofia Triantafillou Ioannis Tsamardinos
We introduce the concept of Automated Causal Discovery (AutoCD), defined as
any system that aims to fully automate the application of causal discovery and
causal reasoning methods. AutoCD's goal is to deliver all causal information
that an expert human analyst would and answer a user's causal queries. We
describe the architecture of such a platform, and illustrate its performance on
synthetic data sets. As a case study, we apply it on temporal telecommunication
data. The system is general and can be applied to a plethora of causal
discovery problems.