Vowpal Wabbit
| Developer(s) | Yahoo! Research & later Microsoft Research |
|---|---|
| Stable release |
8.5.0 / December 2, 2017
|
| Written in | C++ |
| Operating system | Linux, OS-X, Microsoft Windows |
| Type | machine learning |
| License | BSD License |
| Website | hunch |
Vowpal Wabbit (also known as "VW") is an open source fast out-of-core 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 is notable as an efficient scalable implementation of online machine learning with support for a number of machine learning reductions, importance weighting, and a selection of different loss functions and optimization algorithms.
The VW program supports:
Vowpal wabbit has been used to learn a tera-feature (1012) data-set on 1000 nodes in one hour. Its scalability is aided by several factors:
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