Casa Batlo is in Passeig de Gracia or landmarking the expertise space

Task description is crucial not only to every meta-learning enterprise but also to related endeavours like transfer of learning. This paper evaluates the performance of a newly introduced method of task description, landmarking, in a supervised meta-learning scenario. The method relies on correlations between simple and more sophisticated learning algorithms to select the best learner for a task. The results compare favourably with an information-based method and suggest that landmarking holds promise.