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IDDD: An inductive, domain dependent decision algorithm

Moustakis Vasilis, S. Orphanoudakis, G. Charissis, L. Gaga

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URIhttp://purl.tuc.gr/dl/dias/29D53579-23C0-41DC-9F17-06164EF8A8CF-
Αναγνωριστικόhttps://doi.org/10.1007/3-540-56602-3_159-
Γλώσσαen-
ΤίτλοςIDDD: An inductive, domain dependent decision algorithmen
ΔημιουργόςMoustakis Vasilisen
ΔημιουργόςΜουστακης Βασιληςel
Δημιουργός S. Orphanoudakisen
ΔημιουργόςG. Charissisen
ΔημιουργόςL. Gagaen
ΕκδότηςSpringer Verlagen
ΠερίληψηDecision 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.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-04-
Ημερομηνία Δημοσίευσης1993-
Βιβλιογραφική ΑναφοράL. Gaga, V. Moustakis, G. Charissis and S. Orphanoudakis, "IDDD: An Inductive Domain Dependent Algorithm," in European Conference on Machine Learning, 1993, pp. 408-413. doi: 10.1007/3-540-56602-3_159en

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