Title | Improving Multi-label Classifiers via Label Reduction with Association Rules |
Publication Type | Conference Paper |
Year of Publication | 2012 |
Authors | Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. |
Conference Name | 7th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2012) |
Pagination | 188–199 |
Date Published | 9 |
Conference Location | Salamanca (Spain) |
ISBN Number | 978-3-642-28930-9 |
Abstract | Multi-label classification is a generalization of well known problems, such as binary or multi-class classification, in a way that each processed instance is associated not with a class (label) but with a subset of these. In recent years different techniques have appeared which, through the transformation of the data or the adaptation of classic algorithms, aim to provide a solution to this relatively recent type of classification problem. This paper presents a new transformation technique for multi-label classification based on the use of association rules aimed at the reduction of the label space to deal with this problem. |
Notes | TIN2008-06681-C06-02,TIC-3928 |
DOI | 10.1007/978-3-642-28931-6_18 |
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