小编Wal*_*owe的帖子

这应该是非常简单的Keras程序.它一直工作到最后一行代码.但我称之为预测方法.当然,我使用了与训练数据相同的输入数据,但这并不重要.

from keras.models import Sequential
import pandas as pd

url = 'https://raw.githubusercontent.com/werowe/logisticRegressionBestModel/master/KidCreative.csv'

data = pd.read_csv(url, delimiter=',')

labels=data['Buy']
features = data.iloc[:,2:16]

model = Sequential()
model.compile(optimizer='rmsprop' ,loss='binary_crossentropy',metrics=['accuracy'])
model.fit(data, labels, epochs=10, batch_size=32)
model.evaluate(labels, features, batch_size=128)
model.predict(labels)
model.summary()

但我得到这个错误:

model.summary()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/walker/tf3/lib/python3.4/site-packages/keras/engine/network.py", line 1263, in summary
    'This model has never been called, this its weights '
ValueError: This model has never been called, this its weights have not yet been created, so no …