Matches in SemOpenAlex for { <https://semopenalex.org/work/W2609227002> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W2609227002 abstract "Class imbalance is an issue in many real world applications because classification algorithms tend to misclassify instances from the class of interest when its training samples are outnumbered by those of other classes. Several variations of AdaBoost ensemble method have been proposed in literature to learn from imbalanced data based on re-sampling. However, their loss factor is based on standard accuracy, which still biases performance towards the majority class. This problem is mitigated using cost-sensitive Boosting algorithms, although it can be avoided at the outset by modifying the loss factor calculation. In this paper, two loss factors, based on F-measure and G-mean are proposed that are more suitable to deal with imbalanced data during the Boosting learning process. The performance of standard AdaBoost and of three specialized versions for class imbalance (SMOTEBoost, RUSBoost, and RB-Boost) are empirically evaluated using the proposed loss factors, both on synthetic data and on a real-world face re-identification task. Experimental results show a significant performance improvement on AdaBoost and RUSBoost with the proposed loss factors." @default.
- W2609227002 created "2017-05-05" @default.
- W2609227002 creator A5006937759 @default.
- W2609227002 creator A5021089553 @default.
- W2609227002 creator A5067253716 @default.
- W2609227002 date "2016-12-01" @default.
- W2609227002 modified "2023-10-16" @default.
- W2609227002 title "Loss factors for learning Boosting ensembles from imbalanced data" @default.
- W2609227002 cites W1563938718 @default.
- W2609227002 cites W1580049798 @default.
- W2609227002 cites W1909591079 @default.
- W2609227002 cites W1976526581 @default.
- W2609227002 cites W1985074645 @default.
- W2609227002 cites W1988790447 @default.
- W2609227002 cites W2040010062 @default.
- W2609227002 cites W2095148636 @default.
- W2609227002 cites W2096945460 @default.
- W2609227002 cites W2099454382 @default.
- W2609227002 cites W2103614420 @default.
- W2609227002 cites W2104240779 @default.
- W2609227002 cites W2107742354 @default.
- W2609227002 cites W2112076978 @default.
- W2609227002 cites W2119157339 @default.
- W2609227002 cites W2119498311 @default.
- W2609227002 cites W2131046966 @default.
- W2609227002 cites W2153635508 @default.
- W2609227002 cites W2155822698 @default.
- W2609227002 cites W2164330572 @default.
- W2609227002 cites W2171338122 @default.
- W2609227002 cites W2196215201 @default.
- W2609227002 cites W2345243355 @default.
- W2609227002 cites W415041201 @default.
- W2609227002 cites W769353746 @default.
- W2609227002 doi "https://doi.org/10.1109/icpr.2016.7899634" @default.
- W2609227002 hasPublicationYear "2016" @default.
- W2609227002 type Work @default.
- W2609227002 sameAs 2609227002 @default.
- W2609227002 citedByCount "4" @default.
- W2609227002 countsByYear W26092270022018 @default.
- W2609227002 countsByYear W26092270022019 @default.
- W2609227002 crossrefType "proceedings-article" @default.
- W2609227002 hasAuthorship W2609227002A5006937759 @default.
- W2609227002 hasAuthorship W2609227002A5021089553 @default.
- W2609227002 hasAuthorship W2609227002A5067253716 @default.
- W2609227002 hasConcept C119857082 @default.
- W2609227002 hasConcept C12267149 @default.
- W2609227002 hasConcept C124101348 @default.
- W2609227002 hasConcept C141404830 @default.
- W2609227002 hasConcept C153180895 @default.
- W2609227002 hasConcept C154945302 @default.
- W2609227002 hasConcept C41008148 @default.
- W2609227002 hasConcept C45942800 @default.
- W2609227002 hasConcept C46686674 @default.
- W2609227002 hasConceptScore W2609227002C119857082 @default.
- W2609227002 hasConceptScore W2609227002C12267149 @default.
- W2609227002 hasConceptScore W2609227002C124101348 @default.
- W2609227002 hasConceptScore W2609227002C141404830 @default.
- W2609227002 hasConceptScore W2609227002C153180895 @default.
- W2609227002 hasConceptScore W2609227002C154945302 @default.
- W2609227002 hasConceptScore W2609227002C41008148 @default.
- W2609227002 hasConceptScore W2609227002C45942800 @default.
- W2609227002 hasConceptScore W2609227002C46686674 @default.
- W2609227002 hasLocation W26092270021 @default.
- W2609227002 hasOpenAccess W2609227002 @default.
- W2609227002 hasPrimaryLocation W26092270021 @default.
- W2609227002 hasRelatedWork W1556311489 @default.
- W2609227002 hasRelatedWork W1563938718 @default.
- W2609227002 hasRelatedWork W2091007025 @default.
- W2609227002 hasRelatedWork W2095148636 @default.
- W2609227002 hasRelatedWork W2103614420 @default.
- W2609227002 hasRelatedWork W2135493362 @default.
- W2609227002 hasRelatedWork W2170413589 @default.
- W2609227002 hasRelatedWork W220864849 @default.
- W2609227002 hasRelatedWork W2547626803 @default.
- W2609227002 hasRelatedWork W2623640756 @default.
- W2609227002 hasRelatedWork W2762239547 @default.
- W2609227002 hasRelatedWork W2766110499 @default.
- W2609227002 hasRelatedWork W2780616365 @default.
- W2609227002 hasRelatedWork W2794133560 @default.
- W2609227002 hasRelatedWork W2805001156 @default.
- W2609227002 hasRelatedWork W2901360115 @default.
- W2609227002 hasRelatedWork W2917459525 @default.
- W2609227002 hasRelatedWork W3035777675 @default.
- W2609227002 hasRelatedWork W3095245738 @default.
- W2609227002 hasRelatedWork W3168912818 @default.
- W2609227002 isParatext "false" @default.
- W2609227002 isRetracted "false" @default.
- W2609227002 magId "2609227002" @default.
- W2609227002 workType "article" @default.