5-3Keras报错：`Dense` can accept only 1 positional arguments ('units',), but you passed the following positional arguments: [20, 64]

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/

https://www.cnblogs.com/caicaihong/p/5852474.html 详见他人笔记

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()