Cost Sensitive Learning and SMOTE Methods for Imbalanced Data
نویسندگان
چکیده
منابع مشابه
Cost Sensitive Learning of Deep Feature Representations from Imbalanced Data
Class imbalance is a common problem in the case of real-world object detection and classification tasks. Data of some classes are abundant, making them an overrepresented majority, and data of other classes are scarce, making them an underrepresented minority. This imbalance makes it challenging for a classifier to appropriately learn the discriminating boundaries of the majority and minority c...
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ژورنال
عنوان ژورنال: Journal of Applied and Emerging Sciences
سال: 2018
ISSN: 2415-2633,1814-070X
DOI: 10.36785/jaes.81240