AttributeError：“顺序”对象没有属性“得分”

如何解决AttributeError：“顺序”对象没有属性“得分”

我正在使用卷积神经nertworks，而使用顺序我却遇到了训练数据的问题。连续使用不可能获得最佳成绩？

from numpy import array
from numpy import reshape
import numpy as np
def model_CNN(X_train,Y_train,X_test,Y_test):

    model = Sequential()

    model.add(Conv1D(filters=512,kernel_size=32,padding='same',kernel_initializer='normal',activation='relu',input_shape=(256,1)))
    model.add(Conv1D(filters=512,activation='relu'))
    model.add(Dropout(0.2)) # This is the dropout layer. It's main function is to inactivate 20% of neurons in order to prevent overfitting
    model.add(Conv1D(filters=256,activation='relu'))
    model.add(Dropout(0.2))
    model.add(Conv1D(filters=256,activation='relu'))

    model.add(Flatten())

    optimizer = keras.optimizers.SGD(lr=0.01,momentum=0.5)
    model.compile(loss='binary_crossentropy',optimizer=optimizer,metrics=['accuracy'])
    convolutional_model = model.fit(X_train,epochs=5,batch_size=64,verbose=1,validation_data=(X_test,Y_test))
    print(convolutional_model.score(X_train,Y_train))
    model.summary()
    return model

错误被检索为错误提示

AttributeError                            Traceback (most recent call last)
<ipython-input-50-9a2005301144> in <module>()
      1 
----> 2 convolutional_model= model_CNN(X_train,Y_test)
      3 print(convolutional_model)

<ipython-input-49-bac0ec08f100> in model_CNN(X_train,Y_test)
     34     model.compile(loss='binary_crossentropy',metrics=['accuracy'])
     35     convolutional_model = model.fit(X_train,Y_test))
---> 36     print(convolutional_model.score(X_train,Y_train))
     37     # Print the summary of the model
     38     model.summary()

AttributeError: 'Sequential' object has no attribute 'score'

因为我是python的新手，所以我很麻烦并检查了各种资源，但没有帮助，请指导我... 我从这一行中得到了错误

print(convolutional_model.score(X_train,Y_train))

如果不可能，请指导我寻求更好的选择...

解决方法

您应该使用model而不是convolutional_model对象。 fit函数会返回一个历史对象，其中包含一些有关训练阶段的信息，例如损耗，准确性..它取决于损耗函数和度量函数。

你可以试试吗？

print(model.evaluate(X_train,Y_train))