keras.layers.Dropout

# drop out : 뉴런 몇개를 막아버린다.
(X_train,y_train),(X_test,y_test)=mnist.load_data()
X_train=X_train/255
X_test=X_test/255
y_train=np.eye(10)[y_train]
y_test=np.eye(10)[y_test]

from keras.layers import Dropout
from keras.layers import Flatten
model=Sequential()
model.add(Flatten(input_shape=(28,28)))
model.add(Dense(128,activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(256,activation='relu'))
model.add(Dropout(0.5))

model.add(Dense(256,activation='relu'))
model.add(Dense(10,activation='softmax'))

 

model.summary()

 

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
flatten_8 (Flatten)          (None, 784)               0         
_________________________________________________________________
dense_62 (Dense)             (None, 128)               100480    
_________________________________________________________________
dropout_7 (Dropout)          (None, 128)               0         
_________________________________________________________________
dense_63 (Dense)             (None, 256)               33024     
_________________________________________________________________
dropout_8 (Dropout)          (None, 256)               0         
_________________________________________________________________
dense_64 (Dense)             (None, 256)               65792     
_________________________________________________________________
dense_65 (Dense)             (None, 10)                2570      
=================================================================
Total params: 201,866
Trainable params: 201,866
Non-trainable params: 0
_________________________________________________________________

 

# score test
pred_y_test=model.predict(X_test)
(pred_y_test*y_test).sum()/len(y_test)

0.1004556488275528