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()
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