B0773
Title: A compared protocol to improve clustering procedures
Authors: Aurea Grane Chavez - Universidad Carlos III de Madrid (Spain) [presenting]
Marco Riani - University of Parma (Italy)
Silvia Salini - University of Milan (Italy)
Abstract: Two widely used machine learning dimensionality reduction techniques are studied, such as t-SNE and UMAP, in the presence of outliers and/or inliers, with the purpose of understanding whether and how they can be used to improve well-known statistical clustering procedures, such as k-means or t-clust.
