我正在尝试为二进制分类0或1构建RNN / LSTM模型
我的数据集的样本（患者编号，磨时间/秒，X Y和Z的归一化，峰度，偏斜，俯仰，滚动和偏航，标签） .
1,15,-0.248010047716,0.00378335508419,-0.0152548459993,-86.3738760481,0.872322164158,-3.51314800063,0
1,31,-0.248010047716,0.00378335508419,-0.0152548459993,-86.3738760481,0.872322164158,-3.51314800063,0
1,46,-0.267422664673,0.0051143782875,-0.0191247001961,-85.7662354031,1.0928406847,-4.08015176908,0
1,62,-0.267422664673,0.0051143782875,-0.0191247001961,-85.7662354031,1.0928406847,-4.08015176908,0
我试过的 .
import numpy as np
from keras.datasets import imdb
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
from keras.layers import Bidirectional
from keras.preprocessing import sequence
# fix random seed for reproducibility
np.random.seed(7)
train = np.loadtxt("featwithsignalsTRAIN.txt", delimiter=",")
test = np.loadtxt("featwithsignalsTEST.txt", delimiter=",")
x_train = train[:,[2,3,4,5,6,7]]
x_test = test[:,[2,3,4,5,6,7]]
y_train = train[:,8]
y_test = test[:,8]
# create the model
model = Sequential()
model.add(LSTM(20, dropout=0.2, input_dim=6))
model.add(Dense(4, activation = 'sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(x_train, y_train, epochs = 2)
但它给了我以下错误
检查输入时出错：预期lstm_1_input有3个维度，但是有形状的数组（1415684,6）
1 回答
LSTM层采用3维输入，对应于（batch_size，timesteps，features） . 在您的情况下，您只有一个二维输入，即（batch_size，features） .
LSTM层适用于序列格式（句子，股票价格......） . 您需要重新整形数据，以便以这种方式使用它 . 更具体地说，您需要重塑您的数据以使每位患者拥有一条线（或者您可以选择每位患者拥有多个序列，但是我们说我们现在每个患者需要一条线），并且每条线需要包含多个阵列，每个阵列对应于您的患者观察的阵列 .