16 citations · 28 across the 2 of their papers we have counts for
2 papers
stat.CO2023★ 12 cited
Assessing the performance of spatial cross-validation approaches for models of spatially structured data
Michael J Mahoney, Lucas K Johnson, Julia Silge +3
Evaluating models fit to data with internal spatial structure requires specific cross-validation (CV) approaches, because randomly selecting assessment data may produce assessment…
stat.ML2014★ 16 cited
Futility Analysis in the Cross-Validation of Machine Learning Models
Max Kuhn
Many machine learning models have important structural tuning parameters that cannot be directly estimated from the data. The common tactic for setting these parameters is to use r…