[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 20 May – Aurea Grané – Robust Distances for Mixed-type Data

Tuesday, 20 May, 14:30 (WEST)

Universidad Carlos III de Madrid, Spain

Robust distances for mixed-type data

Data scientists address real-world problems using multivariate and heterogeneous datasets, characterized by multiple variables of different natures. Selecting a suitable distance function between units is crucial, as many statistical techniques and machine learning algorithms depend on this concept. Traditional distances, like classical Gower’s or Euclidean, are unsuitable for mixed-type data when underlying correlation or outlying observations are present, and often lead to suboptimal results. In this talk robust distances for mixed-type data will be explored, like robust Generalized Gower’s and robust Related Metric Scaling, as well as their performance in clustering and prediction problems.

Zoom link

https://videoconf-colibri.zoom.us/j/99977463203