Hi Andreas,
I'm wondering: to what extend can we use the warm_start mechanism to do active learning?
The idea would be:
- calling fit on some train dataset
- predict for some additional data and have a user to review those predictions and fix if needed
- warm start, and train again with the initial train dataset extended with the additional annotated data
(Actually, having a notion of prediction confidence would be useful.)
Currently I'm training with OneSlackSSVM. I'm unsure how this algo would deal with this approach ...and your 2009 paper is pretty technical!! :-)
Thanks
JL