Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. Achieving this goal does not imply that these methods automatically deliver good estimators of causal parameters. Examples of such parameters include individual...

Spatial clustering is a fundamental instrument in modern geo-marketing. The complexity of handling of high-dimensional and geo-referenced data in the context of distribution networks imposes important challenges for marketers to catch the right customer segments with useful pattern similarities....

In some applications of supervised machine learning, it is desirable to trade model complexity with greater interpretability for some covariates while letting other covariates remain a "black box". An important example is hedonic property valuation modeling, where machine learning techniques...