Are there any models here that actually implement efficient incremental updates?

[doctorpangloss]

Your docs mention incremental rating prediction as a more efficient way to add data to an existing model:

By incremental training we mean that after each update, the recommender does not perform a complete re-training using all data, but only a brief update procedure taking into account the update and only a subset of the existing training data. This interface does not prevent you from doing a complete re-training when implementing a new class. This makes sense e.g. for simple average-based models.

The question is: do any models actually do a brief update procedure, or do they all do a complete re-training in practice?

Here's my take, looking at implementations only and assuming one additional rating is added to the given model:

• WRMF: Yes, Optimize is only called twice, once on the user and once on the item, and only a single row from the data matrix is fetched in the Optimize call. Also, RetrainItem and RetrainUser are definitely actually called by AddFeedback.
• MostPopular: Yes, but that's not saying much.
• BPRMF: Hard to Say, there's something very fishy going on with the num_item_iterations calculation in RetrainItem that obscures, to me, whether it's actually doing an update, but it appears an effort to make it more efficient was made.
• KNN and its inheritors: Hard to Say. FoldIn appears to be more efficient, but the RetrainUser/RetrainItem implementations seem to do a full retraining because every item/user is revisited and the same calls as done in regular training are made.
• SLIM and its inheritors: No, because AddFeedback isn't overridden and RetrainItem is never called.
• MatrixFactorization and its inheritors: No, because AddRatings base implementation retrains every user and item and no class overrides this method.

[zenogantner]

Hello, BPRMF does perform a brief update, however I would perform additional measurements to see whether everything is tuned correctly before deploying it for anything practical ...

Hint: Feel free to discuss further questions here: mymedialite@googlegroups.com

[doctorpangloss]

Thanks, I think maybe consider throwing NotImplementedException for the ones that definitely do not do incremental updates? Or document otherwise?