神经网络算法：TypeError: `Dense` can accept only 1 positional arguments ('units',), but you passed the following positional arguments: [3, 10]

今天在跑《数据分析和挖掘实战》书上的神经网络算法预测销量高低，由于kmeans已经更新至2.0版本，猜测书中应该还是1.0版本，在设置Dense参数是出现点问题。

import pandas as pd

inputfile = 'C:\\Users\\Administrator\\Data_Minning\\chapter5\\demo\\data\\sales_data.xls'
data = pd.read_excel(inputfile,index_col = u'序号')
data[data == u'好'] = 1
data[data == u'是'] = 1
data[data == u'高'] = 1

data[data != 1 ] = 0
x= data.iloc[:,:3].as_matrix().astype(int)
y=data.iloc[:,3].as_matrix().astype(int)

from keras.models import Sequential
from keras.layers import Dense,Activation

model = Sequential()
model.add(Dense(3,10)) #TypeError 报错
model.add(Activation('relu'))
model.add(Dense(10,1))
model.add(Activation('sigmoid'))
model.compile(loss='binary_crossentropy',optimizer = 'adam')

运行上述代码是时，提示TypeError: `Dense` can accept only 1 positional arguments ('units',), but you passed the following positional arguments: [3, 10]，通过baidu,google搜索问题,对上述代码修改如下，运行成功。

import pandas as pd

inputfile = 'C:\\Users\\Administrator\\Data_Minning\\chapter5\\demo\\data\\sales_data.xls'
data = pd.read_excel(inputfile,index_col = u'序号')
data[data == u'好'] = 1
data[data == u'是'] = 1
data[data == u'高'] = 1

data[data != 1 ] = 0
x= data.iloc[:,:3].as_matrix().astype(int)
y=data.iloc[:,3].as_matrix().astype(int)

from keras.models import Sequential
from keras.layers import Dense,Activation

model = Sequential()
model.add(Dense(10,input_dim=3)) # units=10,input_dim =3
model.add(Activation('relu'))
model.add(Dense(1,input_dim=10)) # units=1,input_dim =10
model.add(Activation('sigmoid'))
model.compile(loss='binary_crossentropy',optimizer = 'adam')