Qualitative induction


Dorian Šuc and Ivan Bratko

Faculty of Computer and Information Science University of Ljubljana, Slovenia

fdorian.suc, ivan.bratkog@fri.uni-lj.si.


Abstract: We consider the problem of automatic construction of qualitative models by inductive learning from quantitative examples. We present an algorithm QUIN (QUalitative INduction) that learns qualitative trees from a set of examples described with numerical attributes. At difference with decision trees that are often used in machine learning, the leaves of qualitative trees contain qualitative functional constraints. A qualitative tree defines a partition of the attribute space into the areas with common qualitative behaviour of the chosen class variable. We demonstrate the use of qualitative trees by their application to the reconstruction of human skill to control container cranes. The induced qualitative trees de ne qualitative control strategies that provide good insight in the human operator's control skill and enable also the reconstruction of individual differences in control styles of different operators.


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