Events Calendar

Colloquium (DSAS) - Wouter Verbeke

Thursday, February 3, 2022
8:30 am - 9:30 am
Virtual via Zoom

Dr. Wouter Verbeke - KU Leuven (website)

"An introduction to causal machine learning for business decision-making"

Machine learning is a powerful tool to support business decision-making. For instance, predictive models can be learned from data to anticipate the future and to make informed decisions, with the eventual objective of optimizing the efficiency and effectiveness of business operations.

Even better than having predictive models, which tell you what will happen, is to have prescriptive models, which tell you what to do so as to optimize the outcome of interest. To this end, prescriptive analytics and operations research develop simulation models, which are typically crafted by an human expert modeler in the form of a series of mathematical equations. As an alternative approach, causal machine learning can be adopted to learn to predict the future as a function of the decisions that are made. In other words, causal machine learning models estimate the net effect on the outcome(s) of interest that would be caused by various potential business decisions. As such, these models directly indicate the optimal decision.

In this talk, I will demonstrate the use and need for causal machine learning by discussing on a business case. I will discuss on the challenges in estimating causal effects and learning a simulation model from data, and introduce some basic causal machine learning methods.

Miranda Fullerton

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