Re-binning is currently implemented as fixed when the dataset is constructed. This is fine for the hyperparameter search, but it would be better to use rebinning as data augmentation when training the final networks.
We will know this new feature is an improvement when:
Compare performance of the data augmentation strategy (with similar ranges of data rebinning) to the previous method (the previous method uses different levels of courseness when sampling rebinning parameters for fixed dataset construction.) Use an F1 score as performance metric.
Re-binning is currently implemented as fixed when the dataset is constructed. This is fine for the hyperparameter search, but it would be better to use rebinning as data augmentation when training the final networks.
We will know this new feature is an improvement when:
Compare performance of the data augmentation strategy (with similar ranges of data rebinning) to the previous method (the previous method uses different levels of courseness when sampling rebinning parameters for fixed dataset construction.) Use an F1 score as performance metric.