MeSH Browser

MeSH Heading: Boosting Machine Learning Algorithms
Tree Number(s): G17.035.250.500.438.500; G17.035.438; L01.224.050.375.530.438.500; L01.224.050.453
Unique ID: D000098404
RDF Unique Identifier: http://id.nlm.nih.gov/mesh/D000098404
Scope Note: A form of ensemble learning methods which combines weak learners to create strong ones, which reduces training errors and bias in the training models. There are different types of boosting such as gradient boosting, XGBoost, and Adaboost.
Entry Term(s): Adaboost; Adaptive Boosting Algorithms; Boosting, Machine Learning; CatBoost; Categorical Boosting; Categorical Boosting Algorithms; Ensemble Machine Learning Boosting; Extreme Gradient Boost; Gradient Boosting Algorithms; Iterative Model Building; Light Gradient Boosting Machine; LightGBM; Machine Learning Boosting Algorithms; XGBoost
Public MeSH Note: 2025
History Note: 2025
Date Established: 2025/01/01
Date of Entry: 2024/08/09
Revision Date: 2023/12/06

Concept UI: M000766606
Scope Note: A form of ensemble learning methods which combines weak learners to create strong ones, which reduces training errors and bias in the training models. There are different types of boosting such as gradient boosting, XGBoost, and Adaboost.
Terms: Boosting Machine Learning Algorithms Preferred Term
Term UI T001140673
Date11/03/2023
LexicalTag NON
ThesaurusID NLM (2025); Machine Learning Boosting Algorithms
Term UI T001141178
Date12/06/2023
LexicalTag NON
ThesaurusID NLM (2025); Boosting, Machine Learning
Term UI T001140675
Date11/03/2023
LexicalTag NON
ThesaurusID NLM (2025); Ensemble Machine Learning Boosting
Term UI T001140674
Date11/03/2023
LexicalTag NON
ThesaurusID NLM (2025)

Boosting Machine Learning Algorithms MeSH Descriptor Data 2025