Incremental/Online training of Models

According to official documentation

“Once a model has been trained, it can be fed previously unseen Examples to produce Predictions of their Outputs”

I’ve only seen the possibility to add new Examples to Dataset using dataset.add(example); but not to Model.

Is this possible and I’m missing something?

[Craigacp]

Yeah, that’s roughly where we expect most people to be. 2 & 3 are roughly equivalent in terms of implementation complexity, but adding new labels has statistical consequences because the new ones will be undertrained relative to the old ones, so we’re thinking about ways to record it and potentially signal it to users.

Mind if I rename this issue? We’ll use it to track the integration of incremental training support.

[2beers]

It would be great even without new features or labels. If I have to set a priority it would be

1. no new features & labels
2. no new features but with new labels
3. with new features and new labels.

But that’s just for my use case. It’s not a priority. I can do a new training if I need to add a different feature/label.