Invariant coordinate selection for multivariate datasets - a guided tour of implementations

Abstract

Invariant Coordinate Selection (ICS) is a powerful unsupervised multivariate method designed to identify the structure of multivariate datasets on a subspace. It relies on the joint diagonalization of two scatter matrices and is particularly relevant as a dimension reduction tool prior to clustering or outlier detection. This workshop is an attempt to present the latest advancements of the different implementations of ICS in different programming languages: R, Python and Julia.