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Extensive semi-quantitative regression.
- Source :
-
Neurocomputing . Dec2016, Vol. 218, p26-36. 11p. - Publication Year :
- 2016
-
Abstract
- In this paper, we propose and solve a new machine learning problem called the extensive semi-quantitative regression, where the information about some target values is incomplete; we only know their lower bounds and/or upper bounds instead of their exact values. To employ the information efficiently in extensive semi-quantitative regression, we introduce a local graph to capture the geometric structure for the samples with the exact target values and the target bounds, and construct a graph-based support vector regressor, called ESQ-SVR. The efficiency of our ESQ-SVR is supported by the results of preliminary experiments conducted on both the artificial and real world datasets. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 218
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 119175061
- Full Text :
- https://doi.org/10.1016/j.neucom.2016.08.073