5 citations · 9 across the 3 of their papers we have counts for
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cs.LG2021★ 5 cited
LCS-DIVE: An Automated Rule-based Machine Learning Visualization Pipeline for Characterizing Complex Associations in Classification
Robert Zhang, Rachael Stolzenberg-Solomon, Shannon M. Lynch +1
Machine learning (ML) research has yielded powerful tools for training accurate prediction models despite complex multivariate associations (e.g. interactions and heterogeneity). I…
cs.LG2020★ 4 cited
A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments
Ryan J. Urbanowicz, Pranshu Suri, Yuhan Cui +4
Machine learning (ML) offers a collection of powerful approaches for detecting and modeling associations, often applied to data having a large number of features and/or complex ass…