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CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests

BACKGROUND: The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve...

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Detaylı Bibliyografya
Yayımlandı:BMC Bioinformatics
Asıl Yazarlar: Ma, Li, Fan, Suohai
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: BioMed Central 2017
Konular:
Online Erişim:https://ncbi.nlm.nih.gov/pmc/articles/PMC5351181/
https://ncbi.nlm.nih.gov/pubmed/28292263
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-017-1578-z
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