Many of the design systems developed in recent years incorporate some machine learning. The number of such systems already available, and the multitude of design learning opportunities that are slowly being revealed, suggest that the time is ripe to attempt to put these developments into a systematic framework. Consequently, in this paper we present a set of dimensions for machine learning in design research. We hope that it can be used as a guide for comparing existing work, and that it may suggest new directions for future exploration in this area.