C++ decision-tree Projects
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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.
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yggdrasil-decision-forests
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Project mention: SIRUS.jl: Interpretable Machine Learning via Rule Extraction | /r/Julia | 2023-06-29SIRUS.jl is a pure Julia implementation of the SIRUS algorithm by Bénard 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.
Project mention: Why do tree-based models still outperform deep learning on tabular data? (2022) | news.ycombinator.com | 2024-03-05Is it this library https://github.com/google/yggdrasil-decision-forests ?
Index
| Project | Stars | |
|---|---|---|
| 1 | LightGBM | 16,043 |
| 2 | yggdrasil-decision-forests | 423 |
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