Over-sampling algorithm for imbalanced data classification
نویسندگان
چکیده
منابع مشابه
Borderline over-sampling for imbalanced data classification
Traditional classification algorithms, in many times, perform poorly on imbalanced data sets in which some classes are heavily outnumbered by the remaining classes. For this kind of data, minority class instances, which are usually much more of interest, are often misclassified. The paper proposes a method to deal with them by changing class distribution through oversampling at the borderline b...
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ژورنال
عنوان ژورنال: JSEE
سال: 2019
ISSN: 1004-4132
DOI: 10.21629/jsee.2019.06.12