Keras IndexError: indices are out-of-bounds

Question

我是 Keras 的新手，我正在尝试在数据集上执行二进制 MLP，并且不知道为什么总是让索引越界。

from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD

model = Sequential()
model.add(Dense(64, input_dim=20, init='uniform', activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(64, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy',
          optimizer='rmsprop')
model.fit(trainx, trainy, nb_epoch=20, batch_size=16) # THROWS INDICES ERROR

错误：

model.fit(trainx, trainy, nb_epoch=20, batch_size=16)

Epoch 1/20
Traceback (most recent call last):

  File "<ipython-input-6-c81bd7606eb0>", line 1, in <module>
model.fit(trainx, trainy, nb_epoch=20, batch_size=16)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\keras\models.py", line 646, in fit
shuffle=shuffle, metrics=metrics)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\keras\models.py", line 271, in _fit
ins_batch = slice_X(ins, batch_ids)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\keras\models.py", line 65, in slice_X
return [x[start] for x in X]

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\keras\models.py", line 65, in <listcomp>
return [x[start] for x in X]

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\pandas\core\frame.py", line 1963, in __getitem__
return self._getitem_array(key)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2008, in _getitem_array
return self.take(indexer, axis=1, convert=True)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\pandas\core\generic.py", line 1371, in take
convert=True, verify=True)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\pandas\core\internals.py", line 3619, in take
indexer = maybe_convert_indices(indexer, n)

  File "C:\Users\Thiru\Anaconda3\lib\site-packages\pandas\core\indexing.py", line 1750, in maybe_convert_indices
raise IndexError("indices are out-of-bounds")

IndexError: indices are out-of-bounds

有人知道为什么会这样吗？我可以运行其他型号就好了

Answer 1

评论中的答案 - trainx 和 trainy 应该是 numpy 数组。您可以使用 as_matrix() 方法将数据框转换为 numpy 数组。我也面临这个问题。奇怪的是 Keras 没有给出有意义的错误信息。

Answer 2

我来这里是为了寻找 auto-sklearn 和 pandas 数据框的相同问题解决方案。解决方案是将 X 数据帧作为 X.values 传递。 IE。适合（X.values，y）

Answer 3

来自official Keras Page:

Keras models are trained on Numpy arrays of input data and labels. For training a model, you will typically use the fit function.

要将 pandas 数据帧转换为 numpy 数组，您可以使用 np.array(dataframe)。例如：

x_train = np.array(x_train)

Keras IndexError: indices are out-of-bounds

Keras IndexError: indices are out-of-bounds

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