Standard SVM often performs poorly on imbalanced datasets for the reason that SVM ignores the tradeoff of the precision between different classes while just takes the overall classification accuracy into account.A new example dependent costs SVM method was proposed

from which we can get more sensitive hyperplane by selecting penalty for every sample according to its corresponding distribution.Experimental results show that this method can efficiently and effectively improve the performance on imbalanced datasets

better than the standard SVM method for comparison.