Software

SMILES extends classical decision tree learners in many ways (new splitting criteria, non-greedy search, new partitions, extraction of several and different solutions), combination (shared ensemble learning), it has an anytime handling of resources, and has a sophisticated and quite effective handling of (misclassification and test) costs. It works as a classifier or a probability estimator, especially designed for ranking (ROC analysis and AUC measures). SMILES can also extract comprehensible models from ensembles of classifiers or from neural networks (through mimicking). Platforms: Unix (Linux), Windows, others.

http://www.dsic.upv.es/~flip/smiles/