神经网络模拟误差

我使用下面也可见的训练数据集“two4”应用下面描述的神经网络。该数据集有150370行。神经网络模拟误差

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)

后我执行仿真，它打破了所有的时间和错误，我得到的样子：

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

你有任何想法可能会导致错误？

来源

2017-04-03 Adriano10

它看起来像标准输出缓冲区由于某种原因关闭。如果您在IDE中执行代码，则可能是您正在关闭控制台窗口，或者IDE正在做一些奇怪的事情。 – nemo

尝试从命令窗口在Spyder之外运行它。同样的问题是否会发生？ – quantummind

Can'c实际上可以在Spyder外运行，因为我已经在Spyder内创建了keras虚拟环境，以便能够模拟神经网络。从cmd运行此代码将不起作用，因为创建的spyder虚拟环境对于此代码运行至关重要。 – Adriano10

你的问题来自发送到大量的数据到standard IO港口在Spyder。这关闭它。尝试设置：

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

现在你可以从e.g恢复epoch指标值：

epoch_loss = history.history["loss"]

一个history.history字典存储保存每个时间段的所有训练的统计数据。

来源

2017-04-04 11:25:28

神经网络模拟误差

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