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Top 8 Gbm Open-Source Projects
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xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
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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.
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.
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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.
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catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Project mention: CatBoost: Open-source gradient boosting library | news.ycombinator.com | 2024-03-05 -
H2O
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
I would use H20 if I were you. You can try out LLMs with a nice GUI. Unless you have some familiarity with the tools needed to run these projects, it can be frustrating. https://h2o.ai/
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Gbm related posts
- CatBoost: Open-source gradient boosting library
- XGBoost 2.0
- XGBoost2.0
- SIRUS.jl: Interpretable Machine Learning via Rule Extraction
- [D] RAM speeds for tabular machine learning algorithms
- Xgboost: Banding continuous variables vs keeping raw data
- [P] LightGBM but lighter in another language?
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A note from our sponsor - SaaSHub
www.saashub.com | 28 Mar 2024
Index
What are some of the best open-source Gbm projects? This list will help you:
Project | Stars | |
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1 | xgboost | 25,438 |
2 | LightGBM | 15,962 |
3 | catboost | 7,684 |
4 | H2O | 6,677 |
5 | glmark2 | 386 |
6 | kodi-standalone-service | 153 |
7 | fairgbm | 95 |
8 | Scoruby | 68 |