  In this paper, we show that conditional inference trees and ensembles are
suitable methods for modeling linguistic variation. As against earlier
linguistic applications, however, we claim that their suitability is strongly
increased if we combine prediction and interpretation. To that end, we have
developed a statistical method, PrInDT (Prediction and Interpretation with
Decision Trees), which we introduce and discuss in the present paper.
