@inproceedings{298,
  author = {Francisco Charte Ojeda and Antonio Jesús Rivera Rivas and Maria José del Jesus Díaz and Francisco Herrera Triguero},
  title = {Improving Multi-label Classifiers via Label Reduction with Association Rules},
  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.},
  year = {2012},
  pages = {188-199},
  month = {9},
  address = {Salamanca (Spain)},
  isbn = {978-3-642-28930-9},
  doi = {10.1007/978-3-642-28931-6_18},
  note = {TIN2008-06681-C06-02,TIC-3928},
}