Beyond model visualization for multidimensional data: high-dimension and complex non numeric data

We greatly appreciate the opportunity to read and discuss the paper “Visualizing statistical models: removing the blindfold” [42]. The article manages to close the gap between statistics and visualization by combining advanced methods from both fields to visualize statistical models and methods. The article provides a very nice overview of visualization tools for statistical models, which can be used to 1) understand the model itself (i.e., what the model says about the data), 2) assess its relevance (i.e., if the model is accurate to describe the data, if the model has been well trained...) and 3) evaluate the variability of a family of models, use this information to select a model within a family, evaluate its robustness and combine several models in a relevant manner.