TY - GEN
T1 - Evidential multi-label classification using the random k-label sets approach
AU - Kanj, Sawsan
AU - Abdallah, Fahed
AU - Denœux, Thierry
PY - 2012
Y1 - 2012
N2 - Multi-label classification deals with problems in which each instance can be associated with a set of labels. An effective multi-label method, named RAkEL, randomly breaks the initial set of labels into smaller sets and trains a single-label classifier in each of this subset. To classify an unseen instance, the predictions of all classifiers are combined using a voting process. In this paper, we adapt the RAkEL approach under the belief function framework applied to set-valued variables. Using evidence theory makes us able to handle lack of information by associating a mass function to each classifier and combining them conjunctively. Experiments on real datasets demonstrate that our approach improves classification performances.
AB - Multi-label classification deals with problems in which each instance can be associated with a set of labels. An effective multi-label method, named RAkEL, randomly breaks the initial set of labels into smaller sets and trains a single-label classifier in each of this subset. To classify an unseen instance, the predictions of all classifiers are combined using a voting process. In this paper, we adapt the RAkEL approach under the belief function framework applied to set-valued variables. Using evidence theory makes us able to handle lack of information by associating a mass function to each classifier and combining them conjunctively. Experiments on real datasets demonstrate that our approach improves classification performances.
UR - http://www.scopus.com/inward/record.url?scp=84860991323&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-29461-7_2
DO - 10.1007/978-3-642-29461-7_2
M3 - Conference contribution
AN - SCOPUS:84860991323
SN - 9783642294600
T3 - Advances in Intelligent and Soft Computing
SP - 21
EP - 28
BT - Belief Functions
T2 - 2nd International Conferenceon Belief Functions
Y2 - 9 May 2012 through 11 May 2012
ER -