신경망 시뮬레이션 오류

Question

아래에서 설명하는 훈련 데이터 세트 "two4"를 사용하여 아래에 설명 된 신경 네트워크를 적용합니다. 데이터 세트에는 150370 개의 행이 있습니다.

30810/100747 [========>.....................]Traceback (most recent call last):.9989  

    File "<ipython-input-1-adb3fdf3bae0>", line 1, in <module> 
    runfile('C:/Users/Dimitris/Desktop/seventh experiment configuration/feedforward_net.py', wdir='C:/Users/Dimitris/Desktop/seventh experiment configuration') 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 714, in runfile 
    execfile(filename, namespace) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 74, in execfile 
    exec(compile(scripttext, filename, 'exec'), glob, loc) 

    File "C:/Users/Dimitris/Desktop/seventh experiment configuration/feedforward_net.py", line 26, in <module> 
    model.fit(X_train, y_train, validation_data=(X_test,y_test), nb_epoch=30, batch_size=10) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\keras\models.py", line 432, in fit 
    sample_weight=sample_weight) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\keras\engine\training.py", line 1106, in fit 
    callback_metrics=callback_metrics) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\keras\engine\training.py", line 830, in _fit_loop 
    callbacks.on_batch_end(batch_index, batch_logs) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\keras\callbacks.py", line 60, in on_batch_end 
    callback.on_batch_end(batch, logs) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\keras\callbacks.py", line 188, in on_batch_end 
    self.progbar.update(self.seen, self.log_values) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\keras\utils\generic_utils.py", line 119, in update 
    sys.stdout.write(info) 

    File "C:\Users\Dimitris\Anaconda2\envs\keras_env\lib\site-packages\ipykernel\iostream.py", line 317, in write 
    self._buffer.write(string) 

ValueError: I/O operation on closed file 

당신이 어떤 생각 어떤 오류가 발생할 수 있나요 : 내가 시뮬레이션을 실행 한 후

from keras.models import Sequential 
from keras.layers import Dense 
from sklearn.cross_validation import train_test_split 
import numpy 
from sklearn.preprocessing import StandardScaler 
# fix random seed for reproducibility 
seed = 7 
numpy.random.seed(seed) 

dataset = numpy.loadtxt("two4.csv", delimiter=",") 
# split into input (X) and output (Y) variables 
X = dataset[:,0:22] 
scaler = StandardScaler() 
X = scaler.fit_transform(X) 
Y = dataset[:,22] 
# split into 67% for train and 33% for test 
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.33,random_state=seed) 
# create model 
model = Sequential() 
model.add(Dense(12, input_dim=22, init='uniform', activation='relu')) 
model.add(Dense(12, init='uniform', activation='relu')) 
model.add(Dense(1, init='uniform', activation='sigmoid')) 
# Compile model 
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) 
# Fit the model 
model.fit(X_train, y_train, validation_data=(X_test,y_test), nb_epoch=30, batch_size=10) 

, 그것은 모든 시간과 내가 좋아하는 외모를 얻을 오류를 분해?

Answer 1

많은 데이터를 Spyder의 standard IO 포트로 보내면 문제가 발생합니다. 이렇게하면 닫힙니다. 설정하려고 :

history = model.fit(X_train, y_train, validation_data=(X_test,y_test), nb_epoch=30, batch_size=10, verbose=0) 

는 이제 예컨대에서 epoch 측정 값을 복구 할 수 있습니다 :

epoch_loss = history.history["loss"] 

history.history DICT 저장 각 시대 저장된 모든 교육 통계를.