LightRiver is an online machine learning library written in Rust. It is meant to be used in high-throughput environments, as well as TinyML systems.
This library is complementary to River. The latter provides a wide array of online methods, but is not ideal when it comes to performance. The idea is to take the algorithms that work best in River, and implement them in a way that is more performant. As such, LightRiver is not meant to be a general purpose library. It is meant to be a fast online machine learning library that provides a few algorithms that are known to work well in online settings. This is a akin to the way scikit-learn and LightGBM are complementary to each other.
cargo run --release --example credit_card
๐๏ธ We plan to implement Aggregated Mondrian Forests.
๐๏ธ We plan to implement Aggregated Mondrian Forests.
๐๏ธ Vowpal Wabbit is very good at recsys via contextual bandits. We don't plan to compete with it. Eventually we want to research a tree-based contextual bandit.
TODO: add a benches
directory
LightRiver is free and open-source software licensed under the 3-clause BSD license.