no code implementations • 5 Jan 2021 • Diego Olaya, Wouter Verbeke, Jente Van Belle, Marie-Anne Guerry
In this article, we therefore extend upon the expected value framework and formally introduce a cost-sensitive decision boundary for double binary causal classification, which is a linear function of the estimated individual treatment effect, the positive outcome probability and the cost and benefit parameters of the problem setting.
no code implementations • 24 Jul 2020 • Wouter Verbeke, Diego Olaya, Jeroen Berrevoets, Sam Verboven, Sebastián Maldonado
The framework is shown to instantiate to application-specific cost-sensitive performance measures that have been recently proposed for evaluating customer retention and response uplift models, and allows to maximize profitability when adopting a causal classification model for optimizing decision-making.