Mini Net Helper Module

Author: Cole Howard

Helper module to create or reinstantiate a neural network. Commented out code is for training the network via Scikit dataset or original MNIST dataset. The resulting network is then pickled and saved to a file. The current uncommented code is for reading that file and reinstantiating it for testing new input against.

mini_net.run_mnist(vector, epochs=0, layers=0, neuron_count=0)

Builds network (or reinstantiates it) based on the MNIST Digits dataset.

Parameters:

• epochs (int) – Number of iterations of the the traininng loop for the whole dataset
• layers (int) – Number of layers (not counting the input layer, but does count output layer)
• neuron_count (list) – The number of neurons in each of the layers (in order), does not count the bias term

mini_net.target_values

list

The possible values for each training vector

mini_net.run_scikit_digits(vector, epochs=0, layers=0, neuron_count=[])

Builds network (or reinstantiates it) based on the Scikit Digits dataset.

Parameters:

• epochs (int) – Number of iterations of the the traininng loop for the whole dataset
• layers (int) – Number of layers (not counting the input layer, but does count output layer)
• neuron_count (list) – The number of neurons in each of the layers (in order), does not count the bias term

mini_net.target_values

list

The possible values for each training vector