Description:
A workbench for knowledge acquisition and data analysis is presented and its use for the classification of business cycles is investigated. Inductive Logic Programming (ILP) allows to model relations between intervals, e.g. time or value intervals. Moreover, the user of the workbench is supported in inspecting the learned rules, not only with respect to their coverage, accuracy, and redundancy, but also regarding consistency (i.e., logical contradictions). The application of ILP requires pre-processing in order to establish time and value intervals. To this end, top-down induction of decision trees is used. This paper describes the workbench MOBAL, its learning algorithm RDT, the preprocessing of data, and the first encouraging results on business cycle data from Germany.