5-3Keras报错：`Dense` can accept only 1 positional arguments ('units',), but you passed the following p

model.add(Dense(20, 64))

Traceback (most recent call last):

 File "", line 1, in model.add(Dense(20, 64))

File "d:\ProgramData\Anaconda3\lib\site-packages\keras\legacy\interfaces.py", line 46, in wrapper str(list(args[1:])))

TypeError: `Dense` can accept only 1 positional arguments ('units',), but you passed the following positional arguments: [20, 64]

序贯模型API - Keras中文文档序贯模型API - Keras中文文档:      

https://keras-cn.readthedocs.io/en/latest/models/sequential/

import pandas as pd

inputfile = 'C:/Users/Administrator/Desktop/data analysis/Python_data_analysis_and_mining/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.core import Dense, Activation

model = Sequential()
model.add(Dense(input_dim=3, output_dim=10))  #添加输入层（3节点）到隐藏层（10节点）的连接
model.add(Activation('relu'))
model.add(Dense(input_dim=10, output_dim=1))  #添加隐藏层（10节点）到输出层（1节点）的连接
model.add(Activation('sigmoid'))

model.compile(loss = 'binary_crossentropy', optimizer='adam')

model.fit(x, y, nb_epoch = 1000, batch_size = 10)
yp = model.predict_classes(x).reshape(len(y))

from cm_plot import *
cm_plot(y,yp).show()

# cm_plot.py 文件,包括了混淆矩阵可视化函数,
# 放置在python的site-packages 目录,供调用
# 例如:~/anaconda2/lib/python2.7/site-packages
#-*- coding: utf-8 -*-
def cm_plot(y, yp):
  from sklearn.metrics import confusion_matrix #导入混淆矩阵函数
  cm = confusion_matrix(y, yp) #混淆矩阵
  import matplotlib.pyplot as plt #导入作图库
  plt.matshow(cm, cmap=plt.cm.Greens) #画混淆矩阵图，配色风格使用cm.Greens，更多风格请参考官网。
  plt.colorbar() #颜色标签
  for x in range(len(cm)): #数据标签
    for y in range(len(cm)):
      plt.annotate(cm[x,y], xy=(x, y), horizontalalignment='center', verticalalignment='center')
  plt.ylabel('True label') #坐标轴标签
  plt.xlabel('Predicted label') #坐标轴标签
  return plt
"""
作者：温故知新的骆驼
链接：https://www.jianshu.com/p/498ea0d8017d
來源：简书
著作权归作者所有。商业转载请联系作者获得授权，非商业转载请注明出处。
"""