Open LeiBAI opened 5 years ago
Hi LeiBAI,
Since I have answered the same question from a phd student, I will simply copy the answer as follows (if you are not proficient in Chinese, I will refine the answer into English, sorry about that):
For Q1 and Q2:
For Q3: A nice suggestion. Since I am no longer in my previous company, I will ask my colleagues for help to publish the codes.
Thanks for your above questions!
@CastleLiang Hi Yuxuan,
Thanks for you patient. According to your reply and my understanding, I got following conclusion:
SO I think only global_attn_state.npy is enough for the input. All others can be generated by this file.
Is my above understanding correct?
Thanks again. Lei
@LeiBAI Hi LeiBAI I have also spent some time studying this project.Your words help me a lot.Thank you very much. But I still wonder the process to the raw data.As the sample_data show,each sensor has provided 19 attributes.So what are these 19 attributes in the raw data (http://urban-computing.com/data/Data-1.zip)? And how to deal with these raw data?If you have some ideas,please help me. Looking forward to your replying anda thank you again! Maple
Hi yoshall,
Thanks for you contribution. I have some question about the code and work. I hope you could give me a hand.
Part 1: According to the sample_data, I think there are 35 nodes, each node generate 19 time series. However, I am a little confusing about the meaning of all input files:
Part 2: Besides I think the model generate prediction for each node separately. Do you train the model for each node separately or train a unified model?
Part 3: a suggestion: I hope you could add some explanation to the input files as they are different to raw inputs and maybe also publish the code process your raw data (http://urban-computing.com/data/Data-1.zip).
Looking forward to your answer and thanks for you patient.