C++ decision-trees

Open-source C++ projects categorized as decision-trees

C++ decision-tree Projects

  • LightGBM

    A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

    Project mention: SIRUS.jl: Interpretable Machine Learning via Rule Extraction | /r/Julia | 2023-06-29

    SIRUS.jl is a pure Julia implementation of the SIRUS algorithm by BĂ©nard et al. (2021). The algorithm is a rule-based machine learning model meaning that it is fully interpretable. The algorithm does this by firstly fitting a random forests and then converting this forest to rules. Furthermore, the algorithm is stable and achieves a predictive performance that is comparable to LightGBM, a state-of-the-art gradient boosting model created by Microsoft. Interpretability, stability, and predictive performance are described in more detail below.

  • yggdrasil-decision-forests

    A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

  • Onboard AI

    Learn any GitHub repo in 59 seconds. Onboard AI learns any GitHub repo in minutes and lets you chat with it to locate functionality, understand different parts, and generate new code. Use it for free at www.getonboard.dev.

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2023-06-29.

Index

Project Stars
1 LightGBM 15,699
2 yggdrasil-decision-forests 390
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