Open tianlianghai opened 1 month ago
Please format your own data according to the guidelines provided in our dataset documentation.
thanks for your reply, but I looked up on the internet and the paper. I don't find how the data is preprocessed. the spatial-temporal shape in NYC bike dataset is [1, 12, 16, 8], I think [16, 8] are the grid size of city given that the city is partitionized. but what does the value mean, the number of the bike? I can't find the related information.
And for the period data [3, 12, 16, 8], what does the value mean in this data. and does it mean every 3 day the data will be the same thing, why the period is 3?
Only by knowing the original information meaning, can I use my own dataset, and do the preprocessing accordingly. Thank you.
I'd like to summarize my question:
The NYC bike dataset you are referring to is sourced from the NYC dataset. It represents bicycle traffic data. The values likely indicate the number of bicycles used in a particular block at a given time.
For example, the dataset, formatted as [3, 12, 16, 8], records data from the past 3 days for the corresponding time slot (one out of 12) for each location (covering $16 \times 8$ grid locations). Here, T is just a pre-defined parameter. UniST is designed to be flexible to different values of T by utilizing an attention mechanism, which adapts to various sequence lengths effectively.
This information should help you understand how to adjust your own dataset preprocessing.
谢谢老师您的指导,结合老师您在README.md中提到的 Shape: (N×T×H×W) Description: o(N): Number of samples o(T): Temporal length o(H): Height of the spatial grid o(W): Width of the spatial grid 可以这样理解[3, 12, 16, 8]分别代表的含义是: [16,8]是城市的网格大小16米 X 8米, 3表示3辆自行车,预测在16米 X 8米的城市网格中会出现的单车数量, 而这里的12 表示在12点, 这样理解对吗? 谢谢老师指点!!
已经在Bike数据集训练和微调好了,使用自己的数据来进行预测呢