Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples - Code and Data

This repository contains the code and data for reproducibility of the paper 'Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples'. 

The following files are included:

Plots: Additional plots not in the paper;

Code: Python scripts to generate trajectories and perform classification/regression;

best_algo.csv : Labels for the classification;

performances.csv : Performances used for the regression;

SA_parameters.csv : SA parameters for all machine learning tasks;

irace_scenario.txt : scenario used for the tuning.