Laboratory for collaborative filtering
This project contains an advanced R implementation of collaborative filtering.
It improves classic implementation, thus making it:
- applicable on large-scale datasets (by calculating predictions partially on matrix chunks) and
- reducing the training time (mostly by using optimized calculations of similarities and k nearest neighbours).
It covers:
- user-based collaborative filtering
- item-based collaborative filtering