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])
# round up and down to check err
if y.layer_out[0] >= 0.5:
temp = 1
else:
temp = 0
# increment the number incorrect if its wrong
if(temp != target[curr_point]):
num_incorrect += 1
