NDLI: Research on ordinal regression of interval valued data

Content Provider	IEEE Xplore Digital Library
Author	Hong Zhu Jun-Hai Zhai Su-Fang Zhang
Copyright Year	2015
Description	Author affiliation: Coll. of Comput. Sci. & Technol., Hebei Univ., Baoding, China (Hong Zhu) \|\| Key Lab. of Machine Learning & Comput. Intell., Hebei Univ., Baoding, China (Jun-Hai Zhai) \|\| Training Div. of Hebei Branch of Meteorol. Cadres Training Inst., China Meteorol. Adm., Baoding, China (Su-Fang Zhang)
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.
Starting Page	866
Ending Page	871
File Size	362361
Page Count	6
File Format	PDF
e-ISBN	9781467372213
DOI	10.1109/ICMLC.2015.7340667
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	monotonie consistency Interval valued data ordinal regression
Content Type	Text
Resource Type	Article

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