Overview

This codebase contains the implementation and evaluation of multiple machine learning models. A total of 13 models have been tested to determine their performance on the given dataset.

Best Model

The model with the highest accuracy is Model 13. Below are the evaluation metrics for Model 13:

• Model Name: Model 13
• Ensemble Method: RandomForestClassifier, StackingClassifier
• Accuracy: 0.9562
• AUROC: 0.8998
• AUPRC: 0.4925
• F1 Score: 0.2953
• MCC: 0.3297

Conclusion

This codebase evaluates 13 different models, with Model 13 achieving the highest accuracy. For more details on the implementation and evaluation, refer to the code and comments within the scripts.