16 citations · 28 across the 19 of their papers we have counts for
3 papers · 1 filter
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…
Visualizations for Bayesian Additive Regression Trees
Alan Inglis, Andrew Parnell, Catherine Hurley
Tree-based regression and classification has become a standard tool in modern data science. Bayesian Additive Regression Trees (BART) has in particular gained wide popularity due i…
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…