In this repository we release all code to replicate all results, tables and figures presented in the paper: HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis

The repository is structured as follows:

• data/ contains raw benchmark data and preprocessed data used for analyses. Note that you can also download the data via syncshare: https://syncandshare.lrz.de/getlink/fiNzyFM7s7jGkCEAzTyjS8/data
• plots/ contains plots as presented in the paper
• tasks/ contains data of all HPO tasks
• ela_splits.csv contains the exact CV splits used for the HPO problems
• run_hpo.R and run_bbob.R contain code to run optimizers on HPO and BBOB problems; run_gensa_ablation contains code to run the GENSA ablation study (see appendix)
  • Job scheduling on HPCs was performed using batchtools
  • If you are interested in the full batchtools registries with all available information, please open an issue
• compute_features_hpo.R and compute_features_bbob.R contain code for computing ELA features on HPO and BBOB problems
• preprocess_hpo.R contains code to preprocess HPO data and visualize surface landscapes
• optimizer_performance.R contains code for the analysis of optimizer performance
• optimizer_performance_gensa.R contains code for the analysis of the GENSA ablation study (see appendix)
• ert.R contains code for the ERT analyses of optimizers
• ela_analysis.R contains code for the analysis of ELA features
• ela_cluster.R contains code for the cluster analysis of ELA features
• predict_kmeans.R contains helper code for predicting in k-means clustering
• tasks_cv_splits.R contains code to generate the CV splits used for the HPO problems
• renv.lock lists the exact R packages that were used on the cluster and can be used for setting up an renv environment
• appendix.pdf is our online appendix

Online Appendix

You can find our appendix here.