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Post‐supervised based learning of feature weight values

Moustakis Vasilis

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URIhttp://purl.tuc.gr/dl/dias/59966E8F-EF16-483A-B262-8C6D8FEBB40B-
Αναγνωριστικόhttps://doi.org/10.1007/11752912_29-
Γλώσσαen-
ΤίτλοςPost‐supervised based learning of feature weight valuesen
ΔημιουργόςMoustakis Vasilisen
ΔημιουργόςΜουστακης Βασιληςel
ΕκδότηςSpringer Verlagen
ΠερίληψηThe article presents in detail a model for the assessment of feature weight values in context of inductive machine learning. Weight assessment is done based on learned knowledge and can not be used to assess feature values prior to learning. The model is based on Ackoff’s theory of behavioral communication. The model is also used to assess rule value importance. We present model heuristics and present a simple application based on the “play” vs. “not play” golf application. Implications about decision making modeling are discussed.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-04-
Ημερομηνία Δημοσίευσης2006-
Βιβλιογραφική ΑναφοράMoustakis, V., "Post‐supervised based learning of feature weight values," in 5th Hellenic Conference of AI Proceedings. Advances in Artificial Intelligence: Proceedings of the 4th Hellenic Conference in AI, Springer, 2006, pp. 279 – 289. doi: 10.1007/11752912_29el

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