This is a self contained feedforward neural network trainer implemented in Processing. It does not require any third party libraries.
If you need a trained neural network in any of your Processing projects all you need to do is:
- Supply your training data. This could be done in multiple different ways (examples provided in ExampleDataSets.pde and Trainer.pde): 2. supply them in a csv file (inputs in "i#" columns, targets in "t#" columns) 3. create them parametrically in your code (see ExampleDataSets.pde and RuleTrainer in Trainer.pde)
- Train your network to the desired error level.
- Save it to a .json file
- Copy saved file along with Matrix.pde and NeuralNetwork.pde to the Processing projects where you want to use it.
An example of this (using RuleTrainer) can be found here