- Feature Normalization: This would ensure that the magnitude of the features is consistent and the impact of the difference in scales is reduced. You can use ‘zscore’ or ‘normalize’ in MATLAB to do this. You can learn more about them from the documentation linked below:
- Data Augmentation: Augment your dataset by creating additional samples with different feature orders. This can be done through ‘randomAffine2d’ or ‘imwarp’ function. You can learn more about them from the documentation:
- Ensemble Method: It is used to train multiple CNN models with different feature orders and combine their predictions. You can use ‘fitcensemble’ function for this. You can find more information about this in the below documentation: