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A machine learning system is useful for extracting models from data that can be used for many applications such as data analysis, decision support or data mining. SMILES is a machine learning system that integrates many different features from other machine learning techniques and paradigms, and more importantly, it presents several innovations in almost all of these features, such as ensemble methods, cost-sensitive learning, and the generation of a comprehensible model from an ensemble. This paper contains a short description of the main features of the system as well as some experimental results.