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I would like to ask whether Avalanche supports continual learning for regression tasks. Most of the examples and templates in the documentation focus on classification problems, but I am particularly interested in applying Avalanche to regression settings, such as time series forecasting or node regression in graphs (e.g., traffic prediction).
If regression is not natively supported, what would be the recommended approach to extend the framework for such tasks? Are there any available examples or best practices for adapting Avalanche to continual learning in regression problems?
The text was updated successfully, but these errors were encountered:
Hello, Avalanche itself supports regression models, so you should be able to use it for your use case. However, there is no official support for regression metrics, so you will have to create your own.
I would like to ask whether Avalanche supports continual learning for regression tasks. Most of the examples and templates in the documentation focus on classification problems, but I am particularly interested in applying Avalanche to regression settings, such as time series forecasting or node regression in graphs (e.g., traffic prediction).
If regression is not natively supported, what would be the recommended approach to extend the framework for such tasks? Are there any available examples or best practices for adapting Avalanche to continual learning in regression problems?
The text was updated successfully, but these errors were encountered: