Welcome to napkinXC’s documentation!¶
Note
Documentation is currently a work in progress!
napkinXC is an extremely simple and fast library for extreme multi-class and multi-label classification that implements the following methods both in Python and C++:
Probabilistic Label Trees (PLTs) - for multi-label log-time training and prediction,
Hierarchical softmax (HSM) - for multi-class log-time training and prediction,
Binary Relevance (BR) - multi-label baseline,
One Versus Rest (OVR) - multi-class baseline.
All the methods decompose multi-class and multi-label into the set of binary learning problems.
Right now, the detailed descirption of methods and their parameters can be found in this paper: Probabilistic Label Trees for Extreme Multi-label Classification