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- W2388620566 abstract "For problem of imbalanced data learning,a gradually learning classification algorithm is proposed.This classification algorithm gradually adds the synthetic minority class examples according to attribute value-range distribution,and removes timely the synthetic examples which the stage classifier misclassifies.As the data achieves the desired degree of balance,the method uses raw data and synthetic data training learning algorithm,and gets the final classifier.Experimental results show that the gradually learning algorithm is better than C4.5,and better than SMOTEBoost and DataBoost-IM on most data sets." @default.
- W2388620566 created "2016-06-24" @default.
- W2388620566 creator A5071278984 @default.
- W2388620566 date "2010-01-01" @default.
- W2388620566 modified "2023-09-25" @default.
- W2388620566 title "Gradually Learning Algorithm for Imbalanced Data" @default.
- W2388620566 hasPublicationYear "2010" @default.
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