Visualizing statistical models: Removing the blindfold

Visualization can help in model building, diagnosis, and in developing an understanding about how a model summarizes data. This paper proposes three strategies for visualizing statistical models: (i) display the model in the data space, (ii) look at all members of a collection, and (iii) explore the process of model fitting, not just the end result. Each strategy is accompanied by examples, including manova , classification algorithms, hierarchical clustering, ensembles of linear models, projection pursuit, self‐organizing maps, and neural networks.