def nfold(meta, data, target, num=10):
total = len(data)
validate = total // num
ix = np.array(data.index)
np.random.shuffle(ix)
test = []
tries = []
nodes = []
for i in range(num):
print 'val with', validate, total
first = ix[:i*validate]
second = ix[(i+1)*validate:]
training = concat([data.loc[first], data.loc[second]])
validating = data.loc[ix[i*validate:(i+1)*validate]]
node = Node(meta, training, target)
tests = node.run()
vals = node.validate(validating)[1]
print tests, vals
test.append(tests)
tries.append(vals)
nodes.append(node)
avg = sum(tries)/len(tries)
print avg
node = Node(meta, data, target)
wrong = node.run()
return avg, wrong, node, test, tries, nodes
