compute_evaluation_results.py

# evaluate Algorithm lb-baseline, lb-sr, lb-srm, 
evaluation_regression_k_prime.py

# evaluate Algorithm lb-rl, lb-srmrl
evaluation_reinforce4lb.py

# compute and plot the evaluation results
compute_evaluation_results.py

# train regression models
train_regression.py

# train RL models
train_reinforce4lb.py

# evaluate Algorithm lb-sr, lb-srm by your own regression model, evaluate lb-baseline 
evaluation_regression_k_prime.py --regression_model_path='path to your own model trained by mixed dataset' # after training, you can select the models from '.results/saved_models/regression/' folder 

# evaluate Algorithm lb-rl, lb-srmrl
evaluation_reinforce4lb.py --rl_model_path='path to your own model' # after training, you can select your models from '.results/saved_models/rl/reinforce/setcovering/' folder

# compute and plot the evaluation results
compute_evaluation_results.py