2 citations · 5 across the 4 of their papers we have counts for
4 papers
vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models
Alan Inglis, Andrew Parnell, Catherine Hurley
We present vivid, an R package for visualizing variable importance and variable interactions in machine learning models. The package provides a range of displays including heatmap…
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models
Alan Inglis, Andrew Parnell, Catherine Hurley
Variable importance, interaction measures, and partial dependence plots are important summaries in the interpretation of statistical and machine learning models. In this paper we d…
Interactive slice visualization for exploring machine learning models
Catherine B. Hurley, Mark O'Connell, Katarina Domijan
Machine learning models fit complex algorithms to arbitrarily large datasets. These algorithms are well-known to be high on performance and low on interpretability. We use interact…
Conditional Visualization for Statistical Models: An Introduction to the condvis Package in R
Mark O'Connell, Catherine B. Hurley, Katarina Domijan
The condvis package is for interactive visualization of sections in data space, showing fitted models on the section, and observed data near the section. The primary goal is the in…