神经网络模拟误差
问题描述:
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)
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?
答
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。
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