Imbalanced Data Optimization Combining K-Means and SMOTE
نویسندگان
چکیده
منابع مشابه
Oversampling for Imbalanced Learning Based on K-Means and SMOTE
Learning from class-imbalanced data continues to be a common and challenging problem in supervised learning as standard classification algorithms are designed to handle balanced class distributions. While different strategies exist to tackle this problem, methods which generate artificial data to achieve a balanced class distribution are more versatile than modifications to the classification a...
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ژورنال
عنوان ژورنال: International Journal of Performability Engineering
سال: 2019
ISSN: 0973-1318
DOI: 10.23940/ijpe.19.08.p17.21732181