Prediction based on integration of decisional DNA and a feature selection algorithm RELIEF-F

Title: Prediction based on integration of decisional DNA and a feature selection algorithm RELIEF-F
Creator: Wang, Peng; Sanín, Cesar; Szczerbicki, Edward
Relation: Cybernetics and Systems Vol. 44, Issue 2-3, p. 173-183
Publisher Link: http://dx.doi.org/10.1080/01969722.2013.762246
Publisher: Taylor & Francis
Resource Type: journal article
Date: 2013
Description: Set of experience knowledge structure (SOEKS) and decisional DNA (DDNA), as a knowledge representation, provide features such as learning from experience, dealing with noisy and incomplete data, making precise decisions, and supporting predictions. In this work, we investigate how the combination of DDNA and SOEKS with feature selection learning algorithm RELIEF-F can improve the quality of predictions. The proposed approach is general and extensible in terms of both designing enhanced learning algorithms and application to other domains.
Subject: data mining; decisional DNA; DDNA; prediction analysis; RELIEF-F; set of experience knowledge structure
Identifier: http://hdl.handle.net/1959.13/1307420
Identifier: uon:21417
Identifier: ISSN:0196-9722
Language: eng
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