为什么 Epoch 显示出相同的准确度？

Question

我正在尝试构建 IDS 入侵检测系统并尝试预测标签是良性还是 DDos。但是我在各个时期都获得了相同的准确性。

代码：

        from tensorflow import keras
    import numpy as np
    import datetime
    import time
    from tensorflow.keras.optimizers import Adam
    from keras.models import Sequential
    from keras.layers import Dense, Dropout
    from keras import callbacks
    x=pd.DataFrame(X)
    x = x.values
    sample = x.shape[0]
    features = x.shape[1]
    #Train: convert 2D to 3D for input RNN
    x_train = np.reshape(x,(sample,features,1)) #shape  = (125973, 18, 1)
    #Test: convert 2D to 3D for input RNN
    x_test=pd.DataFrame(X_test)
    x_test = x_test.values
    x_test = np.reshape(x_test,(x_test.shape[0],x_test.shape[1],1))
Model = keras.Sequential([

        keras.layers.LSTM(80,input_shape=(features,x_train.shape[2]),
                          activation='sigmoid',recurrent_activation='hard_sigmoid'),
        keras.layers.Dense(1,activation="softmax")
    ])

Model.compile(optimizer='rmsprop',loss='mse', metrics=['accuracy'])

#Training the model

Model.fit(x_train, y, epochs=10, batch_size= 32) 
Model.summary()

# Final evaluation of the model
scores = Model.evaluate(x_test, y_test, verbose=0)
print('/n')
print("Accuracy: %.2f%%" % (scores[1]*100))



Epoch 1/10
1074/1074 [==============================] - 92s 83ms/step - loss: 0.4180 - accuracy: 0.5820
Epoch 2/10
1074/1074 [==============================] - 79s 74ms/step - loss: 0.4180 - accuracy: 0.5820
Epoch 3/10
1074/1074 [==============================] - 81s 76ms/step - loss: 0.4180 - accuracy: 0.5820

解决方法是什么？

Answer 1

因为"softmax"激活1个神经元总是输出1。你的神经元不能调整它的输出来减少损失；它在数学上只能 return 1.

为什么 Epoch 显示出相同的准确度？

Why Epoch showing the same accuracy?

machine-learning

deep-learning

lstm

keras

recurrent-neural-network