10 papers
Methods for Quantifying Dataset Similarity: a Review, Taxonomy and Comparison
Marieke Stolte, Franziska Kappenberg, Jörg Rahnenführer +1
Quantifying the similarity between datasets has widespread applications in statistics and machine learning. The performance of a predictive model on novel datasets, referred to as…
Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression
Marieke Stolte, Nicholas Schreck, Alla Slynko +4
Simulation is a crucial tool for the evaluation and comparison of statistical methods. How to design fair and neutral simulation studies is therefore of great interest for research…
Improving Adaptive Seamless Designs through Bayesian optimization
Jakob Richter, Tim Friede, Jörg Rahnenführer
We propose to use Bayesian optimization (BO) to improve the efficiency of the design selection process in clinical trials. BO is a method to optimize expensive black-box functions,…
Adjusted Measures for Feature Selection Stability for Data Sets with Similar Features
Andrea Bommert, Jörg Rahnenführer
For data sets with similar features, for example highly correlated features, most existing stability measures behave in an undesired way: They consider features that are almost ide…
Feature Selection Methods for Cost-Constrained Classification in Random Forests
Rudolf Jagdhuber, Michel Lang, Jörg Rahnenführer
Cost-sensitive feature selection describes a feature selection problem, where features raise individual costs for inclusion in a model. These costs allow to incorporate disfavored…
Implications on Feature Detection when using the Benefit-Cost Ratio
Rudolf Jagdhuber, Jörg Rahnenführer
In many practical machine learning applications, there are two objectives: one is to maximize predictive accuracy and the other is to minimize costs of the resulting model. These c…