Vowpal Wabbit
Vowpal Wabbit is an open-source fast online interactive machine learning system library and program developed originally at Yahoo! Research, and currently at Microsoft Research. It was started and is led by John Langford. Vowpal Wabbit's interactive learning support is particularly notable including Contextual Bandits, Active Learning, and forms of guided Reinforcement Learning. Vowpal Wabbit provides an efficient scalable out-of-core implementation with support for a number of machine learning reductions, importance weighting, and a selection of different loss functions and optimization algorithms.Notable features
The VW program supports:
Vowpal wabbit has been used to learn a tera-feature data-set on 1000 nodes in one hour. Its scalability is aided by several factors:
- Out-of-core online learning: no need to load all data into memory
- The hashing trick: feature identities are converted to a weight index via a hash
- Exploiting multi-core CPUs: parsing of input and learning are done in separate threads.
- Compiled C++ code
