Right now, this package includes Online Gradient Descent Logistic Regression (OGDLR) and Follow the (proximal) Regularized Leader (FTRLprox) algorithms.
Some features:
- The methods work with extremely sparse data (all treated categorically) by using dictionary for storage or hashing trick. This allows to train very sparse feature sets without exhausting memory.
- The interface is similar to that of scikit learn.
- Cross-validation is made on the fly.
All this is work in progress, use at your own risk.
For paper, see here.