Ensemble noisy label detection on MNIST

In this paper machine learning methods are studied for classification data containing some misleading items. We use ensembles of known noise correction preprocessing the training set. Preprocessing can be either relabeling or deleting items detected to have noisy labels. After preprocessing, usual convolutional networks applied data. With performance very accurate further improved.