Probability density function estimation based over-sampling for imbalanced two-class problems

A novel probability density function (PDF) estimation based over-sampling approach is proposed for two-class imbalanced classification problems. The Parzen-window kernel function is applied to estimate the PDF of the positive class, from which synthetic instances are generated as additional training... View More