lightgbm: Light Gradient Boosting Machine

Canonical link: https://rscholar.com/pkg/lightgbm

Yu Shi • Guolin Ke • Damien Soukhavong • James Lamb • Qi Meng • Thomas Finley • Taifeng Wang • Wei Chen • Weidong Ma • Qiwei Ye • Tie-Yan Liu • Nikita Titov • Yachen Yan • Microsoft Corporation • Dropbox • Alberto Ferreira • Daniel Lemire • Victor Zverovich • IBM Corporation • David Cortes • Michael Mayer • View description and downloads View dependencies GitHub project

2020 Published

0 Citations

21 Authors

16 Revisions

4.6.0 Version

MIT License

Referenced by ⇅	Year
predhy.GUI: Genomic Prediction of Hybrid Performance with Graphical User Interface (Version 2.1.1)	2023
treeshap: Compute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP' Algorithm (Version 0.4.0)	2023
fastml: Guarded Resampling Workflows for Safe and Automated Machine Learning in R (Version 0.7.6)	2024
BORG: Bounded Outcome Risk Guard for Model Evaluation (Version 0.2.5)	2026
EIX: Explain Interactions in 'XGBoost' (Version 1.2.1)	2019
FoRecoML: Forecast Reconciliation with Machine Learning (Version 1.0.0)	2026
MFF: Meta Fuzzy Functions (Version 0.1.0)	2026
PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model (Version 6.5.1)	2025
SHAPforxgboost: SHAP Plots for 'XGBoost' (Version 0.2.0)	2019
bonsai: Model Wrappers for Tree-Based Models (Version 0.4.0)	2022
cbl: Causal Discovery under a Confounder Blanket (Version 0.1.3)	2022
comets: Covariance Measure Tests for Conditional Independence (Version 0.2-2)	2024
fastshap: Fast Approximate Shapley Values (Version 0.1.1)	2019
funcml: Functional Machine Learning Framework (Version 0.7.1)	2026
misspi: Missing Value Imputation in Parallel (Version 0.1.0)	2023
ml: Supervised Learning with Mandatory Splits and Seeds (Version 0.1.2)	2026
mlS3: Unified S3 Interface to Machine Learning Models (Version 0.1.0)	2026
mllrnrs: R6-Based ML Learners for 'mlexperiments' (Version 0.0.8)	2023
predhy.GUI Interface: (Version )	0
predhy: Genomic Prediction of Hybrid Performance (Version 2.1.2)	2019
qeML: Quick and Easy Machine Learning Tools (Version 1.1)	2023
qshap: Fast Calculation of Feature Contributions in Boosting Trees (Version 1.0)	2026
r2pmml: Convert R Models to 'PMML' (Version 0.31.0)	2019
rtemis: Machine Learning and Visualization (Version 1.0.0)	2026
sae.projection: Small Area Estimation Using Model-Assisted Projection Method (Version 0.1.5)	2024
shapviz: SHAP Visualizations (Version 0.10.3)	2022
sits Cubes: (Version )	0
stackgbm: Stacked Gradient Boosting Machines (Version 0.1.0)	2024
ubair: Effects of External Conditions on Air Quality (Version 1.1.1)	2025
vip: Variable Importance Plots (Version 0.4.5)	2018

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