Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How to evaluate over multiple csv files #32

Open
tionry opened this issue Oct 25, 2024 · 1 comment
Open

How to evaluate over multiple csv files #32

tionry opened this issue Oct 25, 2024 · 1 comment

Comments

@tionry
Copy link

tionry commented Oct 25, 2024

Hi,
Thanks for your work!
I tried to use your code for our dataset model training/validating. I meet several issues:
1. how to train over multiple csv files, I see that the sh command --data-name-list gives file_name, how to write the command if
I want to train over multiple files, such as AQShunyi-1.csv, AQShunyi-2.csv simutenously?
2. How may I train my prediction model as the hyperparameters are predefined in the command line, or I must train the mode lat somewhere else?
3. Can the framework deal with data of multiple features, e.g., if I want to forecast the nationwide air quality, assume I get data from different regions, the data may look like [region, timestamp, quality], it is time series with 'region' feature, so the question is how to train and also validate the prediction model, or it is infeasible in the context of time series forecasting.
Looking forward to your reply, thanks so much!

@qiu69
Copy link
Collaborator

qiu69 commented Oct 25, 2024

Thank you for your attention and questions!
Regarding the first question, we currently do not support it, but we had plans to implement this function (global forecasting).
I didn't understand the last two questions! Can we exchange WeChat for easier communication? My WeChat: qxf780310. Look forward to hearing from you.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants