This paper describes our work on the Sisyphus challenge dataset, which includes both classification and clustering tasks. We present our work in the context of the CRISP-DM methodology. Further key aspects of the work are the evaluation and integration of multiple models by means of ROC analysis. We indicate a simple method of forcing classifiers to cover the whole of the ROC space. In conclusion, we outline several promising research directions.