Vowpal Wabbit is a machine learning system that pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning. There is a specific focus on reinforcement learning with several contextual bandit algorithms implemented and the online nature lending to the problem well. Vowpal Wabbit is a destination for implementing and maturing state-of-the-art algorithms with performance in mind. The input format for the learning algorithm is substantially more flexible than might be expected. Examples can have features consisting of free-form text, which is interpreted in a bag-of-words way. There can even be multiple sets of free-form text in different namespaces. Similar to the few other online algorithm implementations out there. There are several optimization algorithms available with the baseline being sparse gradient descent (GD) on a loss function.

Features

  • Input Format
  • Scalability
  • Speed
  • Feature Interaction
  • Install with a package manager
  • Subsets of features can be internally paired

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

C++

Related Categories

C++ Machine Learning Software, C++ Reinforcement Learning Frameworks, C++ Reinforcement Learning Libraries, C++ Reinforcement Learning Algorithms

Registered

2022-05-27