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Causal Simulations for Uplift Modeling

2019/02/01 by Jeroen Berrevoets, Berrevoets, Jeroen, Wouter Verbeke +1 · 2 citations
Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #Auction Theory and Applications

paper · pdf · doi:10.48550/arxiv.1902.00287

Abstract

Uplift modeling requires experimental data, preferably collected in random fashion. This places a logistical and financial burden upon any organisation aspiring such models. Once deployed, uplift models are subject to effects from concept drift. Hence, methods are being developed that are able to learn from newly gained experience, as well as handle drifting environments. As these new methods attempt to eliminate the need for experimental data, another approach to test such methods must be formulated. Therefore, we propose a method to simulate environments that offer causal relationships in their parameters.

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