attrs.append(row[1:])
if __name__ == '__main__':
print "Parsing the training dataset..."
# parse the training dataset and store its information into globals
parse_data('mushroom-training.txt')
# set up the layers to be used
x = Layer(6, attrs[curr_point], 1)
y = Layer(1, x.layer_out, 2)
print "Begining training the neural network:"
# iterate through to train the neural network
while total_runs < NUM_TRAINING_ITERATIONS:
# set the new input values
x.input_vals = attrs[curr_point]
# set up the first layer and evaluate it
x.input_vals = attrs[curr_point]
x.eval()
# set up the second layer and evaluate it
y.input_vals = x.layer_out
y.eval()
# backpropogate
y.backprop(target[curr_point])
x.backprop(y)
# get the current error
curr_err = err(y.layer_out[0], target[curr_point])
