Model assessment

In data mining and machine learning, models come from data and provide insights for understanding data (unsupervised classification) or making prediction (supervised learning) (Giudici, 2003, Hand, 2000). Thus the scientific status of this kind of models is different from the classical view where a model is a simplified representation of reality provided by an expert of the field. In most data mining applications a good model is a model which not only fits the data but gives good predictions, even if it is not interpretable (Vapnik, 2006).