Beyond multidimensional data in model visualization: High-dimensional and complex nonnumeric data
Résumé
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. Here, we want to discuss further two important challenges for visualization of statistical methods in modern data and problems: the first one is the issue of dimension reduction and the second one is the issue of non numeric data sets.
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