The folder "Step_2_Pathway" contains information on our ensemble algorithm experiment. The folder ending with "A" is the ensemble algorithm, the folder ending with "C" is the random sequence, the "Naive-SW" is the "Stack SW", the "Hierarchical-SW" is the "Stach HSW", and the "NSGA-II_Retraining" is the "Stack GA".
The 3 example selection strategies (SW, HSW, GA), and the 4 objectives (maximising CR, CBA, OBA, OF1) are also shown in these codes. The same functions were used in Experiments in Section 4.

The older "AutoGeTS" contains the original model M0 and the code used to train M0. The synthetic data would be disclosed later after the approval of the data provider. Sorry that the original data "tickets_topics.csv" is owned by the company so we are not allowed to disclose it. Thus, we have removed confidential information and placed others in "Train_PCA_YZ_withPred_0".

Required packages: 
pip install catboost==1.2.5 inspyred==1.0.2 joblib==1.1.0 matplotlib==3.4.3 matplotlib-inline==0.1.7 numpy==1.26.4 "nvidia-ml-py==12.555.43" pandas==2.2.2 plotly==5.22.0 psutil==5.8.0 scikit-learn==0.24.2 openpyxl