We are encountering an issue where the NBS-Predict algorithm is not learning effectively when using the default tutorial data and parameters. The output consistently shows average AUC scores around 0.5, which suggests that the model is not performing better than random chance.
Results: The algorithm consistently returned AUC scores around 0.5. With the default tutorial data and parameters, I expected the algorithm to learn effectively and provide AUC scores significantly different from 0.5, but the following is the MATLAB command window output:
ESTIMATOR: LogReg
Searching Algorithm: bayesOpt
METRIC: auc
Number of Folds: 10
Number of Repetitions: 10
-------------
| Score |
-------------
| 0.490 |
| 0.496 |
| 0.475 |
| 0.498 |
| 0.507 |
| 0.490 |
| 0.506 |
| 0.507 |
| 0.498 |
| 0.500 |
-------------
10x10 repeated-CV: µScore: 0.497, σScore: 0.010
The elapsed time is 61.308250 seconds.
Permutation testing is running! Permutations: 1000
The confusion matrix also showed that the predictions were not reflect correct true positive and true negative values
![image](https://private-user-images.githubusercontent.com/148017632/299160399-527f0c4b-ada0-40eb-b490-8b913c4066d3.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MTkwMjE0OTEsIm5iZiI6MTcxOTAyMTE5MSwicGF0aCI6Ii8xNDgwMTc2MzIvMjk5MTYwMzk5LTUyN2YwYzRiLWFkYTAtNDBlYi1iNDkwLThiOTEzYzQwNjZkMy5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNjIyJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDYyMlQwMTUzMTFaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1mNmI5ZDYxY2JiNWI2ZjA4MTBiYzdkZmRlNDc5MDE0NDVmZjYxYTI3YzFiYzE4MTZkOTQ1Y2I3ZjNlN2QwMmUwJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.vLMcG8qihoWulsahtpFpXiXrjqFKvN7JBx7vyP6v3Ik)
![image](https://private-user-images.githubusercontent.com/148017632/299160454-486ac5cb-17d2-46fe-80b5-bd3e901e3993.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MTkwMjE0OTEsIm5iZiI6MTcxOTAyMTE5MSwicGF0aCI6Ii8xNDgwMTc2MzIvMjk5MTYwNDU0LTQ4NmFjNWNiLTE3ZDItNDZmZS04MGI1LWJkM2U5MDFlMzk5My5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNjIyJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDYyMlQwMTUzMTFaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0yMjIyNTQ1YTBkMDBjZjhiZTljYjUxZDFmMjk3NTgxZTMyZTliZmM5NTZhY2UyZDQ0YmExMzY0ZGJhNDkwMWQ3JlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.pcobmJE96nJPPDtecsYpVJjDX4BVZZL0uyHpR-hWdSE)
To note: We have not modified the default settings or data in any significant way. The issue persists even after repeating the analysis on different computers with different OS, Matlab versions with different parameters.
Is there a known issue with the current version of NBS-Predict that might be causing this behaviour?
Could there be an issue with the data, the choice of model/hyperparameters, or a potential bug in the software?
Any assistance or guidance you could provide would be greatly appreciated.