| Method | UNLABEL | LABEL |
|---|---|---|
| SVM | 0.6981 | 0.7020 |
| RNN | 0.8078 | 0.8104 |
| KNN | 0.8567 | 0.8574 |
| CNN | 0.9097 | 0.9187 |
| MBAA-CNN | 0.9897 | 0.9909 |
- Training
python main.py- Deployment
python Model_Apply.py-
Provide preprocessed Ten bacterial Raman spectrum test files for testing, and our pretrained Classification model . When using it, please extract the test file to the Final_Data folder and modify the file path in Model_Apply.py. For original data labels, you can set up a dictionary yourself, for example:
['Cns', 'E. cloacae', 'E. coli', 'K. pneumoniae', 'MC', 'MRSA', 'MSSA', 'P. aeruginosa', 'P. vulgaris', 'S. epidermidi']
- It is recommended to use a Linux environment to create a virtual environment for training
Please indicate the source for use!
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