我正在尝试使用keras运行基于神经网络的模型 哪个numpy数组可用作训练数据和标签的输入。 数据最初存储在文本文件中，长0/1 序列不是逗号分隔的，我读过 包含65行和7116列的numpy数组。
print('X.shape ', X.shape)
X.shape (65, 7116)
print('X \n ', X)
X
[['0' '1' '0' ... '0' '0' '0']
['1' '0' '0' ... '0' '0' '0']
['1' '0' '0' ... '0' '0' '0']
...
['0' '0' '1' ... '0' '0' '0']
['1' '0' '0' ... '0' '0' '0']
['0' '0' '1' ... '0' '0' '0']]
X是我当前输入的数据 print（'type（X）'，type（X）） 类型（X）
print('type(X[0]) ', type(X[0]))
type(X[0]) <class 'numpy.ndarray'>
print('type(X[0][0]) ', type(X[0][0]))
type(X[0][0]) <class 'numpy.str_'>
现在type(X[0][0])是<class 'numpy.str_'>而不是浮动的，
我不能将其用作NN的输入。
我使用了以下方法，但是这些给出了错误
X1 = X.astype(float) # ValueError: could not convert string to float: 'Y'
x1 = np.asarray(X, dtype=float) # ValueError: could not convert string to float: 'Y'
X1 = np.array(X)
np.float_(X1) # ValueError: could not convert string to float: 'Y'
print('X1 ', X1)
如何对其进行转换，以便可以将其用作NN的输入。
输出Y已经被替换：
Y = Y.reshape((65,1)) # Y was in pandas data frame originally
print(type(Y)) # <class 'numpy.ndarray'>
print(Y.shape) # (65, 1)
model = Sequential()
model.add(Dense(4000, input_dim=7116, activation='relu'))
model.add(Dense(1000, activation='relu'))
model.add(Dense(200, activation='relu'))
model.add(Dense(50, activation='relu'))
model.add(Dense(1, activation='linear'))
model.compile(loss='mean_squared_error', optimizer='adam')
model.fit(X, Y, verbose=2)
Currently the fit function says:
Epoch 1/10
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-45-344e05f836de> in <module>()
10 model.compile(loss='mean_squared_error', optimizer='adam')
11
---> 12 model.fit(X, Y, verbose=2)
D:\Installed_Programs\anaconda3\lib\site-packages\keras\models.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
861 class_weight=class_weight,
862 sample_weight=sample_weight,
--> 863 initial_epoch=initial_epoch)
864
865 def evaluate(self, x, y, batch_size=32, verbose=1,
D:\Installed_Programs\anaconda3\lib\site-packages\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
1428 val_f=val_f, val_ins=val_ins, shuffle=shuffle,
1429 callback_metrics=callback_metrics,
-> 1430 initial_epoch=initial_epoch)
1431
1432 def evaluate(self, x, y, batch_size=32, verbose=1, sample_weight=None):
D:\Installed_Programs\anaconda3\lib\site-packages\keras\engine\training.py in _fit_loop(self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch)
1077 batch_logs['size'] = len(batch_ids)
1078 callbacks.on_batch_begin(batch_index, batch_logs)
-> 1079 outs = f(ins_batch)
1080 if not isinstance(outs, list):
1081 outs = [outs]
D:\Installed_Programs\anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in __call__(self, inputs)
2266 updated = session.run(self.outputs + [self.updates_op],
2267 feed_dict=feed_dict,
-> 2268 **self.session_kwargs)
2269 return updated[:len(self.outputs)]
2270
D:\Installed_Programs\anaconda3\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
898 try:
899 result = self._run(None, fetches, feed_dict, options_ptr,
--> 900 run_metadata_ptr)
901 if run_metadata:
902 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
D:\Installed_Programs\anaconda3\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1102 feed_handles[subfeed_t] = subfeed_val
1103 else:
-> 1104 np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
1105
1106 if (not is_tensor_handle_feed and
D:\Installed_Programs\anaconda3\lib\site-packages\numpy\core\numeric.py in asarray(a, dtype, order)
490
491 """
--> 492 return array(a, dtype, copy=False, order=order)
493
494
ValueError: could not convert string to float: 'Y'
我检查了numpy数组的各个元素之间是否有空格/ Nan /其他字符。但是没有这种类型的元素可能导致此错误。所以我想这是引起问题的numpy数组的字符串元素。
提前谢谢！！