pandas Keras 神经网络错误：使用序列设置数组元素
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Keras Neural Network Error: Setting an Array Element with a Sequence
提问by Ashley O
I'm loading dummy data into a neural network, but I'm receiving an error I can't seem to debug:
我正在将虚拟数据加载到神经网络中，但我收到了一个似乎无法调试的错误：
Here is my data, visualized:
这是我的数据，可视化：
df:
Label Mar
0 | [[.332, .326], [.058, .138]]
0 | [[.234, .246], [.234, .395]]
1 | [[.084, .23], [.745, .923]],
I'm trying to use the 'Mar' column to predict the 'Label' column (I know this data makes no sense, its just similar to my real data). Here is my neural network code:
我正在尝试使用 'Mar' 列来预测 'Label' 列（我知道这个数据没有意义，它只是类似于我的真实数据）。这是我的神经网络代码：
model = Sequential()
model.add(Dense(3, input_dim=(1), activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
X = df['Mar']
Y = pd.get_dummies(df['Label'])
model.fit(X, Y, epochs=150, batch_size=10)
Here is the code to create my sample data:
这是创建我的示例数据的代码：
Sample = [{'Label': 0, 'Mar': [[.332, .326], [.058, .138]]},
{'Label': 0, 'Mar': [[.234, .246], [.013, .592]]},
{'Label': 1, 'Mar': [[.084, .23], [.745, .923]]}]
df = pd.DataFrame(Sample)
When I get to the final row of this code, I get this error:
当我到达此代码的最后一行时，出现此错误：
Epoch 1/150
-----------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-271-3d2506918d89> in <module>()
----> 1 model.fit(X, Y, epochs=150, batch_size=10)
/usr/local/lib/python2.7/site-packages/keras/models.pyc in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
854 class_weight=class_weight,
855 sample_weight=sample_weight,
--> 856 initial_epoch=initial_epoch)
857
858 def evaluate(self, x, y, batch_size=32, verbose=1,
/usr/local/lib/python2.7/site-packages/keras/engine/training.pyc in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
1496 val_f=val_f, val_ins=val_ins, shuffle=shuffle,
1497 callback_metrics=callback_metrics,
-> 1498 initial_epoch=initial_epoch)
1499
1500 def evaluate(self, x, y, batch_size=32, verbose=1, sample_weight=None):
/usr/local/lib/python2.7/site-packages/keras/engine/training.pyc in _fit_loop(self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch)
1150 batch_logs['size'] = len(batch_ids)
1151 callbacks.on_batch_begin(batch_index, batch_logs)
-> 1152 outs = f(ins_batch)
1153 if not isinstance(outs, list):
1154 outs = [outs]
/usr/local/lib/python2.7/site-packages/keras/backend/tensorflow_backend.pyc in __call__(self, inputs)
2227 session = get_session()
2228 updated = session.run(self.outputs + [self.updates_op],
-> 2229 feed_dict=feed_dict)
2230 return updated[:len(self.outputs)]
2231
/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
776 try:
777 result = self._run(None, fetches, feed_dict, options_ptr,
--> 778 run_metadata_ptr)
779 if run_metadata:
780 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
952 np_val = subfeed_val.to_numpy_array()
953 else:
--> 954 np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
955
956 if (not is_tensor_handle_feed and
/usr/local/lib/python2.7/site-packages/numpy/core/numeric.pyc in asarray(a, dtype, order)
529
530 """
--> 531 return array(a, dtype, copy=False, order=order)
532
533
ValueError: setting an array element with a sequence.
I now suspect it has something to do with my input columns being list, not np arrays? However, I've tried making them into arrays first and I'm still getting the same error. Would really love and appreciate help!!
我现在怀疑它与我的输入列是列表有关，而不是 np 数组？但是，我尝试先将它们放入数组中，但仍然遇到相同的错误。真的很喜欢并感谢帮助！
EditI've tried one hot encoding the label field, as I found somewhere online that that may help. It hasn't helped at this point
编辑我已经尝试了一种热编码标签字段，因为我在网上找到了可能有帮助的地方。这在这一点上没有帮助
采纳答案by maxymoo
A couple of issues here,
这里有几个问题，
- The input is the wrong shape
- The input is a mixture of arrays and lists.
- 输入是错误的形状
- 输入是数组和列表的混合。
One possible solution would be to use keras.layers.Flattento reshape your data, and pd.Series.tolist()to uniformize the data type of the input array:
一种可能的解决方案是用于keras.layers.Flatten重塑数据，并pd.Series.tolist()统一输入数组的数据类型：
model = Sequential()
model.add(Flatten(input_shape=(2,2)))
model.add(Dense(3, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
X = df['Mar'].tolist()
Y = df['Label']
model.fit(X, Y, epochs=150, batch_size=10)
