Semi-Supervised Cascaded Clustering for Classification of Noisy Label Data. (arXiv:2205.02209v1 [cs.LG])

Web: http://arxiv.org/abs/2205.02209

The performance of supervised classification techniques often deteriorates
when the data has noisy labels. Even the semi-supervised classification
approaches have largely focused only on the problem of handling missing labels.
Most of the approaches addressing the noisy label data rely on deep neural
networks (DNN) that require huge datasets for classification tasks. This poses
a serious challenge especially in process and manufacturing industries, where
the data is limited and labels are noisy. We propose a semi-supervised cascaded
clustering (SSCC) algorithm …

arxiv classification clustering data semi-supervised