A Hybrid Undersampling-SMOTE Method for Imbalanced Big Data Classification

Imbalanced data is an important issues and challenges faced in data classification. This will lead to poor performance of binary classifiers, this is due to bias in classification in favour of the majority class and lack of understanding of the influence of the minority class, while the minority cla...

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Principais autores:	Shaymaa Ahmed Razoqi, Ghayda Al-Talib
格式:	Artigo
語言:	Inglês
出版:	University of Mosul, College of Education for Pure Science 2023-12-01
叢編:	مجلة التربية والعلم
主題:	big data,, ,،classification,, ,،imbalanced problem,, ,،resampling,, ,،clustering
在線閱讀:	https://edusj.mosuljournals.com/article_180971_2e8e268f4bdbc7d511ffb728d5b70f64.pdf
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