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Found 4 papers, 2 papers with code
On the Assessment of Benchmark Suites for Algorithm Comparison
In this paper, we propose the use of an item response theory (IRT) model, the Bayesian two-parameter logistic model for multiple attempts, to statistically evaluate these aspects with respect to the empirical success rate of algorithms.
Bayesian Paired-Comparison with the bpcs Package
This article introduces the bpcs R package (Bayesian Paired Comparison in Stan) and the statistical models implemented in the package.
Methodology Mathematical Software
Machine Learning Algorithms for Data Labeling: An Empirical Evaluation
While many of these algorithms are available in open-source packages, there is no research that investigates how these algorithms compare to each other in different types of datasets and with different percentages of available labels.
Statistical Models for the Analysis of Optimization Algorithms with Benchmark Functions
The online appendix provides a step-by-step guide on how to perform the analysis of the models discussed in this paper, including the code for the statistical models, the data transformations and the discussed tables and figures.
Methodology
