Post supervised based learning of feature weight values

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Abstract

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. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Moustakis, V. S. (2006). Post supervised based learning of feature weight values. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3955 LNAI, pp. 279–289). Springer Verlag. https://doi.org/10.1007/11752912_29

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