3 ms·
You could give the user an option to specify that the CSV file represents equally-spaced time series data, in which case you fit a time series model to predict
by Bostonian 5y ago
You could give the user an option to specify that the CSV file represents equally-spaced time series data, in which case you fit a time series model to predict the target column.
- nitsky 5y agoGreat idea! We definitely want to do this. We have an open issue to track it: https://github.com/tangramdotdev/tangram/issues/28 https://github.com/tangramdotdev/tangram/issues/28.
- Bostonian 5y agoGood. A further thought is that if you allow time series models, you could allow the user to specify a time column in addition to the column of the response variable. Then you can fit seasonal time series models to the data.
- nitsky 5y agoYes! What we have in mind is this: `tangram train --file data.csv --target price --date date` This would predict the "price" column, using the date in the "date" column. Internally, we can generate features from the date column like "hour of day", "day of week", "season", etc. that can help the model learn periodic patterns. Thanks for the great suggestion.