Constructing Confidence Intervals for 'the' Generalization Error -- a
Comprehensive Benchmark Study
Constructing Confidence Intervals for 'the' Generalization Error -- a
Comprehensive Benchmark Study
When assessing the quality of prediction models in machine learning, confidence intervals (CIs) for the generalization error, which measures predictive performance, are a crucial tool. Luckily, there exist many methods for computing such CIs and new promising approaches are continuously being proposed. Typically, these methods combine various resampling procedures, most …