... | ... | @@ -9,6 +9,3 @@ Clus is a decision tree and rule induction system that implements the [predictiv |
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Classification and regression trees are special cases of PCTs, and by choosing the right parameter settings Clus can closely mimic the behavior of tree learners such as [CART](http://www.amazon.com/Classification-Regression-Trees-Leo-Breiman/dp/0412048418) or [C4.5](http://www.amazon.com/C4-5-Programs-Machine-Learning-Kaufmann/dp/1558602380). However, its applicability goes well beyond classical classification or regression tasks: Clus has been successfully applied to many different tasks including multi-task learning (multi-target classification and regression), structured output learning, multi-label classification, hierarchical classification, and time series prediction. Next to these supervised learning tasks, PCTs are also applicable to semi-supervised learning, subgroup discovery, and clustering. In a similar way, predictive clustering rules or PCRs generalize [classification rule sets](http://portal.acm.org/citation.cfm?id=112163) and also apply to the aforementioned learning tasks.
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Clus is co-developed by the [Declarative Languages and Artificial Intelligence](http://dtai.cs.kuleuven.be/) group of the [Katholieke Universiteit Leuven](http://www.kuleuven.be/), Belgium, and the [Department of Knowledge Technologies](http://kt.ijs.si/) of the [Jožef Stefan Institute](http://www.ijs.si/), Ljubljana, Slovenia. It is written in Java and is open-source software licensed under the [GPL](http://www.gnu.org/licenses/gpl.html). |
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[[http://www.kuleuven.be/|{{logo_kul.png}}]] [[http://www.ijs.si/|{{logo_ijs.png}}]] |
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