activity
20182022
most citedVisualizations for Bayesian Additive Regression Trees

2 citations · 4 across the 5 of their papers we have counts for

collaborators

6 papers

cs.SD20221 cited

NEAL: An open-source tool for audio annotation

Anthony Gibbons, Ian Donohue, Courtney E. Gorman +2

Passive acoustic monitoring is used widely in ecology, biodiversity, and conservation studies. Data sets collected via acoustic monitoring are often extremely large and built to be…

stat.ME2022

Review of Clustering Methods for Functional Data

Mimi Zhang, Andrew Parnell

Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying the discrete measurements/observations. Application of functio…

stat.CO20222 cited

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…

stat.CO20211 cited

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…

eess.SP2019

Real-Time Anomaly Detection for Advanced Manufacturing: Improving on Twitter's State of the Art

Caitríona M. Ryan, Andrew Parnell, Catherine Mahoney

The detection of anomalies in real time is paramount to maintain performance and efficiency across a wide range of applications including web services and smart manufacturing. This…

cs.LG2018

An Evaluation of Methods for Real-Time Anomaly Detection using Force Measurements from the Turning Process

Yuanzhi Huang, Eamonn Ahearne, Szymon Baron +1

We examined the use of three conventional anomaly detection methods and assess their potential for on-line tool wear monitoring. Through efficient data processing and transformatio…