Clus is a decision tree and rule induction system that implements the predictive clustering framework. This framework unifies unsupervised clustering and predictive modeling and allows for a natural extension to more complex prediction settings such as multi-task learning and multi-label classification. While most decision tree learners induce classification or regression trees, Clus generalizes this approach by learning trees that are interpreted as cluster hierarchies. We call such trees predictive clustering trees or PCTs. Depending on the learning task at hand, different goal criteria are to be optimized while creating the clusters, and different heuristics will be suitable to achieve this.
