我有29个特征变量进行时序分类，DL模式和NAS模式模型出错

czstudio commented 1 year ago

ValueError: in user code:

File "d:\learn\Anaconda3\envs\py3.8\lib\site-packages\keras\engine\training.py", line 1160, in train_function  *
    return step_function(self, iterator)
File "d:\learn\Anaconda3\envs\py3.8\lib\site-packages\keras\engine\training.py", line 1146, in step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "d:\learn\Anaconda3\envs\py3.8\lib\site-packages\keras\engine\training.py", line 1135, in run_step  **
    outputs = model.train_step(data)
File "d:\learn\Anaconda3\envs\py3.8\lib\site-packages\keras\engine\training.py", line 993, in train_step

...

ValueError: Input 0 of layer "TS-NAS" is incompatible with the layer: expected shape=(None, 256, 6), found shape=(128, 256, 29)

zhangxjohn commented 1 year ago

您好，您的数据格式转换成panel形式了吗？

数据格式：https://hyperts.readthedocs.io/en/latest/contents/0300_dataformat.html

zhangxjohn commented 1 year ago

从错误看，网络输入层未识别出您传入了29维特征的数据，识别成了6维，您可以详细说一下您的数据吗？

DataCanvasIO / HyperTS

我有29个特征变量进行时序分类，DL模式和NAS模式模型出错 #61