An implementation of backpropagation for a multilayer perceptron network with (at most) one hidden layer. Note that data must be discrete-valued.
Completed as coursework for Williams College CSCI 374: Machine Learning.
The following command trains and evaluates the MLP net on the given .arff
file:
python3 test.py -L 0.3 -E 300 -K 10 -H 5 NominalData/titanic.arff
For this example, -L 0.3 specifies a learning rate of 0.3, -E 300 specifies
training for 300 epochs, -K 10 specifies 10-fold cross validation, and -H 5
specifies 5 units in the hidden layer.
Running python3 test.py -h will also display the default values for these
parameters.