Support vector machine has a better classification and prediction performance on balance
data classification, but has a poor performance for imbalance data. In this paper, the reason …

This paper describes a new learning strategy on the problem of classification on overlapped
and imbalanced training set. We devise an adaptive scheme for minority generating; with …

SVM was widely used in fault diagnosis, and achieved good results. However, the
unbalance between normal sample datasets and fault sample datasets made it very difficult …

SVM is not as favored for large-scale data training as for Network Intrusion Detection
because the training complexity of SVM is highly dependent on the size of training sample …

Support Vector Machine (Support Vector Machine, SVM) demonstrates many unique
advantages in solving the small sample, nonlinear and high dimensional pattern …