About: LightGBM

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LightGBM, short for light gradient-boosting machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and scalability.

Attributes	Values
rdf:type	Thing software schema:CreativeWork work wikidata:Q386724 Software
rdfs:label	LightGBM (en) LightGBM (ja)
rdfs:comment	LightGBM, short for light gradient-boosting machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and scalability. (en) LightGBMは、Light Gradient Boosting Machine の略で、機械学習用のフリーかつオープンソースの分散型勾配ブースティングフレームワークであり、マイクロソフトが開発した。決定木アルゴリズムをベースにしており、ランク付け、分類、その他の機械学習タスクに使用される。パフォーマンスとスケーラビリティに重点を置いて開発されている。 (ja)
foaf:name	LightGBM (en)
foaf:homepage	https://lightgbm.readthedocs.io/
name	LightGBM (en)
foaf:depiction
dcterms:subject	2016 software Applications of artificial intelligence Free and open-source software Microsoft free software Software using the MIT license Applied machine learning Data mining and machine learning software Microsoft Research Open-source artificial intelligence
Wikipage page ID	64785522 (xsd:integer)
Wikipage revision ID	1121122742 (xsd:integer)
Link from a Wikipage to another Wikipage	Python (programming language) Scikit-learn Decision tree 2016 software Applications of artificial intelligence Free and open-source software Microsoft free software Software using the MIT license GitHub Linux ML.NET MacOS Machine learning C++ C (programming language) C Sharp (programming language) Applied machine learning Data binning Windows Learning to rank Data mining and machine learning software Gradient boosting Random forest Microsoft Research Microsoft Microsoft Research Microsoft Windows Open-source artificial intelligence R (programming language) XGBoost MIT License Statistical classification GBDT Gradient-Boosted Regression Trees Gradient Boosting Machine Free and open source Multiple Additive Regression Trees
Link from a Wikipage to an external page	https://lightgbm.readthedocs.io/ https://www.apress.com/gp/book/9781484256688%7Cpublisher=Apress%7Cisbn=978-1-4842-5668-8%7Cyear=2020 https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf%7Cyear=2017 https://www.microsoft.com/en-us/research/project/lightgbm/ https://github.com/microsoft/LightGBM
sameAs	LightGBM LightGBM LightGBM
dbp:wikiPageUsesTemplate	dbt:Cite_book dbt:Cite_document dbt:Infobox_software dbt:Microsoft_FOSS dbt:Microsoft_Research dbt:Portalbar dbt:Reflist dbt:Short_description dbt:Start_date_and_age dbt:Compu-AI-stub
thumbnail	wiki-commons:Special:FilePath/LightGBM_logo_black_text.svg?width=300
author	Guolin Ke / Microsoft Research (en)
developer	Microsoft and LightGBM contributors (en)
genre	Machine learning, gradient boosting framework (en)
latest release date	2022-01-06 (xsd:date)
latest release version	v3.3.2 (en)
license	MIT License
logo	250 (xsd:integer)
operating system	Linux MacOS Microsoft Windows
programming language	Python (programming language) C++ C (programming language) R (programming language)
repo	https://github.com/microsoft/LightGBM
website	https://lightgbm.readthedocs.io/
has abstract	LightGBM, short for light gradient-boosting machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and scalability. (en) LightGBMは、Light Gradient Boosting Machine の略で、機械学習用のフリーかつオープンソースの分散型勾配ブースティングフレームワークであり、マイクロソフトが開発した。決定木アルゴリズムをベースにしており、ランク付け、分類、その他の機械学習タスクに使用される。パフォーマンスとスケーラビリティに重点を置いて開発されている。 (ja)

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