Title :
Research on ordinal regression of interval valued data
Author :
Hong Zhu;Jun-Hai Zhai;Su-Fang Zhang
Author_Institution :
College of Computer Science and Technology, Hebei University, Baoding, 071002, Hebei, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
Traditional regression algorithms can only deal with non-ordinal regression problems of crisp data. In order to deal with the problem of the regression of interval valued data with the monotonic constraint, an algorithm is proposed in this paper, where the condition attributes are ordinal interval values and the decision attribute is continuous. The proposed algorithm employs the combination of the variance and rank mutual information as heuristic. The advantage of the proposed algorithm is that it can consider both the dispersion degree of the decision attribute value and the monotonie consistency degree that between condition attributes and decision attribute.
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2015 International Conference on
DOI :
10.1109/ICMLC.2015.7340667