Visualizing statistical models: removing the blindfold

Hadley Wickham, Dianne Cook, Heike Hofmann

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)203-225
Number of pages23
JournalStatistical Analysis and Data Mining
Volume8
Issue number4
DOIs
Publication statusPublished - Aug 2015
Externally publishedYes

Keywords

  • model visualization
  • Exploratory data analysis
  • data mining
  • classification
  • high-dimensional data

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