Is there a way to save Dataset()?
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- Python
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Description
I have a trained model saved as a pickle file. My model has both user and item features.
When I load the model, I can make predictions for seen users by calling
pickled_model.predict(user_ids = [0], item_ids =[0])
But, I want to adjust it to a cold start problem, making predictions for new users. In this case, it requires to have dataset.fit_partial() , where the dataset should be fitted in the old dataset. It there a way to save and retrieve the dataset? Or we need to refit it every time before calling fit_partial()
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Research direction
No file or test is named. Start by locating the Dataset class and its fit_partial workflow, then check how model serialization currently handles related state. Done means establishing and documenting a supported way to preserve the fitted dataset for cold-start predictions, or clearly recording that refitting is required.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100