1 citations · 2 across the 5 of their papers we have counts for
6 papers
Colour Blinded by the Noise
Harriet Mason, Rachel Rogers, Alison Kleffner +1
Uncertainty visualisation is important for data transparency, especially for map visualisations where data is often aggregated. Despite the importance of this area, studies evaluat…
Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web
Weihao Li, Dianne Cook, Emi Tanaka +2
Visual assessment of residual plots is a common approach for diagnosing linear models, but it relies on manual evaluation, which does not scale well and can lead to inconsistent de…
A Mathematical Framework and Software Implementation for Uncertainty Visualisation
Harriet Mason, Dianne Cook, Sarah Goodwin +1
Random variables are the bread and butter of statistics, and visualisations are one of the most versatile tools in the field, so it is a wonder why we do not have a methodology for…
An Enhanced Projection Pursuit Tree Classifier with Visual Methods for Assessing Algorithmic Improvements
Natalia da Silva, Dianne Cook, Eun-Kyung Lee
This paper presents enhancements to the projection pursuit tree classifier and visual diagnostic methods for assessing their impact in high dimensions. The original algorithm uses…
The Noisy Work of Uncertainty Visualisation Research: A Review
Harriet Mason, Dianne Cook, Sarah Goodwin +2
Better representation of the uncertainty in a data visualisation is a focus of recent research activity. A problem with the current literature is that there is a lack of clarity ab…
Automated Assessment of Residual Plots with Computer Vision Models
Weihao Li, Dianne Cook, Emi Tanaka +2
Plotting the residuals is a recommended procedure to diagnose deviations from linear model assumptions, such as non-linearity, heteroscedasticity, and non-normality. The presence o…