This section contains the code for all the other models in Table 7 in Appendix D.  
Please modify the location of the data in the code according to the location of your data. 

1.MLP: Run python mlp.py

2.Random_forest：Run python random_forest.py

3.Decision_tree：Run python decision_tree.py

4.LASSO：Run python LASSO.py

5.Elastic_Net：Run python Elastic_Net.py

6.KAN：Run python kan.py, Before you run kan.py, follow this link (https://github.com/KindXiaoming/pykan) to learn how to use kan and download the necessary package.
pip install pykan
python==3.9.7
matplotlib==3.6.2
numpy==1.24.4
scikit_learn==1.1.3
setuptools==65.5.0
sympy==1.11.1
torch==2.2.2
tqdm==4.66.2

7.CNN+KAN:Run python CNN+KAN.py, As with the above steps, please follow the link (https://github.com/KindXiaoming/pykan) to learn how to use kan.

8.CNN+MLP:Run python cnn+mlp.py

9.GCN: 
 Run python image_merger.py merges the data from the training set and the test set separately.
 Run python get_grop_data.py to get feature.npy and label.npy.
 Run python overall.py to get train_edge.npy and test_edge.npy.
 Run python train.py train to train the model, Run python train.py test to test.
 
9.Transformer: Run python main.py train to to train the model, Run python main.py test to test.