Post‐supervised based learning of feature weight values

URI	http://purl.tuc.gr/dl/dias/59966E8F-EF16-483A-B262-8C6D8FEBB40B	-
Αναγνωριστικό	https://doi.org/10.1007/11752912_29	-
Γλώσσα	en	-
Τίτλος	Post‐supervised based learning of feature weight values	en
Δημιουργός	Moustakis Vasilis	en
Δημιουργός	Μουστακης Βασιλης	el
Εκδότης	Springer Verlag	en
Περίληψη	The 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
Τύπος	Πλήρης Δημοσίευση σε Συνέδριο	el
Τύπος	Conference Full Paper	en
Άδεια Χρήσης	http://creativecommons.org/licenses/by/4.0/	en
Ημερομηνία	2015-11-04	-
Ημερομηνία Δημοσίευσης	2006	-
Βιβλιογραφική Αναφορά	Moustakis, 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_29	el

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