Visualizing statistical models: Removing the blindfold. (16th July 2015)

• Record Type: Journal Article
• Authors: Wickham, Hadley; Cook, Dianne; Hofmann, Heike
• Is Part Of: Statistical analysis and data mining. Volume 8:Number 4(2015)
• Page Start: 203
• Page End: 225
• Publication Date: 2015-07-16
• Subjects: Data mining -- Statistical methods -- Periodicals; 006.312
• DOI: 10.1002/sam.11271
• Languages: English
• ISSNs: 1932-1864

Abstract

<abstract abstract-type="main" id="sam11271-abs-0001"> <title>Abstract</title> <p id="sam11271-para-0001">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 <sc>manova</sc>, classification algorithms, hierarchical clustering, ensembles of linear models, projection pursuit, self‐organizing maps, and neural networks.</p> </abstract>