写一个cnn-lstm回归代码
时间: 2024-01-20 15:03:54 浏览: 30
好的,这是一个涉及机器学习的技术问题,我可以帮您解答。以下是一个简单的CNN-LSTM回归代码示例,供参考:
```
import tensorflow as tf
from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, LSTM, Dense, Flatten
# Define model architecture
input_shape = (28, 28, 1)
time_steps = 10
num_classes = 1
inputs = Input(shape=(time_steps,) + input_shape)
x = Conv2D(32, kernel_size=(3, 3), activation='relu')(inputs)
x = MaxPooling2D(pool_size=(2, 2))(x)
x = Flatten()(x)
x = LSTM(64)(x)
outputs = Dense(num_classes, activation='sigmoid')(x)
model = tf.keras.Model(inputs=inputs, outputs=outputs)
model.compile(loss='mean_squared_error', optimizer='adam')
# Train the model
x_train = ...
y_train = ...
model.fit(x_train, y_train, epochs=10)
# Test the model
x_test = ...
y_test = ...
model.evaluate(x_test, y_test)
```
请注意,此代码仅是示例。您需要根据自己的数据集和任务进行适当修改。
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