我有类似以下的输入:
[
[1, 2, 3]
[4, 5, 6]
[7, 8, 9]
...]
数据的形状为(1, num_samples, num_features)
,标签的格式如下:
[
[0, 1]
[1, 0]
[1, 0]
...]
数组的形状为(1, num_samples, 2)
。
然而,当我尝试运行以下Keras代码时,出现了以下错误:ValueError: Error when checking model target: expected dense_1 to have 2 dimensions, but got array with shape (1, 8038, 2)
。从我所读的内容来看,这似乎源于我的标签是二维的,而不仅仅是整数。如果是这样,我该如何在Keras中使用one-hot标签?
以下是代码:
num_features = 463
trX = np.random(8038, num_features)
trY = # one-hot array of shape (8038, 2) as described above
def keras_builder(): #generator to build the inputs
while(1):
x = np.reshape(trX, (1,) + np.shape(trX))
y = np.reshape(trY, (1,) + np.shape(trY))
print(np.shape(x)) # (1, 8038, 463)
print(np.shape(y)) # (1, 8038, 2)
yield x, y
model = Sequential()
model.add(LSTM(100, input_dim = num_features))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit_generator(keras_builder(), samples_per_epoch = 1, nb_epoch=3, verbose = 2, nb_worker = 1)
这将立即抛出上述错误:
Traceback (most recent call last):
File "file.py", line 35, in <module>
model.fit_generator(keras_builder(), samples_per_epoch = 1, nb_epoch=3, verbose = 2, nb_worker = 1)
...
ValueError: Error when checking model target: expected dense_1 to have 2 dimensions, but got array with shape (1, 8038, 2)
谢谢!