training

Code for training supervised learning algorithms

There are three main parts of the training:

1. Data sampling 📁 (row-based methods) or default training 📁 (image-based methods)
2. Hyperparameter tuning 📁
3. Final training 📁

See the individual folders for more information.

Everything except the final training uses validationObjFcn to do the actual training. validationObjFcn trains on the training dataset and tests on the validation data. The final training functions train on the combination of the training and validation data.