SMOGN: a Pre-processing Approach for Imbalanced Regression

By Paula Branco, Luís Torgo, Rita P. Ribeiro. LIDTA@PKDD/ECML, 2017

309 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5839b2b19bf85a7b02b5bdabb752dae2993131ca

Citations in the corpus

• Delving into Deep Imbalanced Regression (2021, unknown): “…S MOTE R and SMOGN, we divide the target range based on a manually defined relevance method, under-sample majority regions, and over-sample minority regions by either interpolating with selected nearest neighbors (Torgo et al., 2013) or also adding Gaussian noise perturbation (Branco et al., 2017).”