2 citations · 6 across the 5 of their papers we have counts for
5 papers
Predicting Mycotoxin Contamination in Irish Oats Using Deep and Transfer Learning
Alan Inglis, Fiona Doohan, Subramani Natarajan +13
Mycotoxin contamination poses a significant risk to cereal crop quality, food safety, and agricultural productivity. Accurate prediction of mycotoxin levels can support early inter…
Machine Learning Applied to the Detection of Mycotoxin in Food: A Review
Alan Inglis, Andrew Parnell, Natarajan Subramani +1
Mycotoxins, toxic secondary metabolites produced by certain fungi, pose significant threats to global food safety and public health. These compounds can contaminate a variety of cr…
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…