data = np.genfromtxt("raw CVR.csv", delimiter=",")
reps = 100
performance = []
train_size = 35
test_size = 400
total_elems = range(len(data))
train_elems = r.sample(total_elems, train_size)
test_elems = [x for x in total_elems if x not in train_elems]
single_err = 0
start = time.time()
for rep in range(reps):
test_net = Net(len(data[0, 0:-2]), 1, 3, 3, 3)
for n in xrange(1000):
train_err = 0
accuracy = 0
for i in train_elems:
single_err = test_net.err(data[i, 0:-2], data[i, -1])
output = test_net.feedforward(data[i, 0:-2])[0]
if abs(output - data[i, 0]) < 1:
accuracy += 1
print "SINGLE RUN ERR: %f" % (single_err)
train_err += single_err
train_err /= len(train_elems)
accuracy = float(accuracy) / train_size
print "MEAN RUN ERR: %f\n" % (train_err)
print "MEAN RUN ACC: %f\n" % (accuracy)
raw_input("Enter...")
