Model Assessment for Predictive Classification Models
In this article, we present a novel methodology to assess predictive models for a binary target. In our opinion, the main weakness of the criteria proposed in the literature is not to take the financial costs of a wrong decision into account. The objective of this article is to derive the optimal cut-off in predictive classification models and to improve model assessment on the basis of a general class of loss functions. We describe how our proposal performs in a real application on credit scoring.