1. 读取数据
data= open(\'e:/java_ws/scalademo/data/sample_naive_bayes_data.txt\' , \'r\')
2. 把数据随机分割为training集 和test集
def SplitData(data,max,ind,seed): ## seed is always be 11L
test=[]
train=[]
random.seed(seed)
for line in data:
if random.randint(0,max)==ind: ## if a random int between 0 and max is ind, then put this line in test Set
test.append(\'\'.join(line))
else:
train.append(\'\'.join(line))
return train,test
3. 按分割符拆分一个数据集
def parseData(data,delimiter1,delimiter2): # delimiter1 是拆开X,Y; delimiter2 是拆开Y的每个元素
x=[]
y=[]
for line in data:
parts = line.split(delimiter1)
x1 = [float(a) for a in parts[1].split(delimiter2)]
y1 = float(parts[0])
##print x1,y1
x.append(x1)
y.append(y1)
return x,y