IDDD: An inductive, domain dependent decision algorithmIDDD: An inductive, domain dependent decision algorithm Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-11-041993enDecision tree induction, as supported by id3, is a well known approach of heuristic classification. In this paper we introduce mother-child relationships to model dependencies between attributes which are used to represent, training examples. Such relationships are implemented via iddd which extends the original id3 algorithm. The application of iddd is demonstrated via a series of concept acquisition experiments using a ‘real-world’ medical domain. Results demonstrate that the application of iddd contributes to the acquisition of more domain relevant knowledge as compared to knowledge induced by id3 itself.http://creativecommons.org/licenses/by/4.0/408-413European Conference on Machine Learning Moustakis Vasilis Μουστακης Βασιλης S. Orphanoudakis G. Charissis L. Gaga Springer Verlag