Abstract This package provides a hyperparameter optimization (HPO) benchmark based on a Support Vector Machine classifier (sklearn.svm.SVC). Each evaluation trains the SVM with stratified k-fold cross-validation on a small dataset that ships with scikit-learn, and returns the mean classification error (1 - accuracy), which is minimized.
The benchmark is useful for testing samplers on a real machine learning task that runs in seconds on a laptop, without downloading any data or precomputed tables.