Evaluating Uplift Models

CAUSAL DATA SCIENCE

How to compare and select the best uplift model

One of the most widespread applications of causal inference in the industry is uplift modeling, a.k.a. the estimation of Conditional Average Treatment Effects.

When estimating the causal effect of a treatment (a drug, ad, product, …) on an outcome of interest (a disease, firm revenue, customer satisfaction, …), we are often not only interested in understanding whether the treatment works on average, but …

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