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Selective oversampling approach for strongly imbalanced data

Challenges posed by imbalanced data are encountered in many real-world applications. One of the possible approaches to improve the classifier performance on imbalanced data is oversampling. In this paper, we propose the new selective oversampling approach (SOA) that first isolates the most represent...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:PeerJ Comput Sci
Egile Nagusiak: Gnip, Peter, Vokorokos, Liberios, Drotár, Peter
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: PeerJ Inc. 2021
Gaiak:
Sarrera elektronikoa:https://ncbi.nlm.nih.gov/pmc/articles/PMC8237317/
https://ncbi.nlm.nih.gov/pubmed/34239981
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.604
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