URI | http://purl.tuc.gr/dl/dias/59966E8F-EF16-483A-B262-8C6D8FEBB40B | - |
Identifier | https://doi.org/10.1007/11752912_29 | - |
Language | en | - |
Title | Post‐supervised based learning of feature weight values | en |
Creator | Moustakis Vasilis | en |
Creator | Μουστακης Βασιλης | el |
Publisher | Springer Verlag | en |
Content Summary | 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 |
Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
Type of Item | Conference Full Paper | en |
License | http://creativecommons.org/licenses/by/4.0/ | en |
Date of Item | 2015-11-04 | - |
Date of Publication | 2006 | - |
Bibliographic Citation | 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 |