Gradient boosting machines, a tutorial

10.3389/fnbot.2013.00021

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Bibliographic Details
Main Authors:	Natekin, A, Knoll, A
Other Authors:	MECHANICAL ENGINEERING
Format:	Article
Published:	2020
Subjects:	adaboost loss function article classification algorithm conceptual framework custom base learner function decision tree electromyogram electromyograph electrode explanatory variable gradient boosting machine learning human learning algorithm linear regression analysis logistic regression analysis loss function machine learning Markov random field mathematical parameters methodology pattern recognition physical activity random forest response variable robotics smooth model statistical model support vector machine wavelet analysis
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/181584
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-181584
record_format	dspace
spelling	sg-nus-scholar.10635-1815842024-04-04T02:35:43Z Gradient boosting machines, a tutorial Natekin, A Knoll, A MECHANICAL ENGINEERING adaboost loss function article classification algorithm conceptual framework custom base learner function decision tree electromyogram electromyograph electrode explanatory variable gradient boosting machine learning human learning algorithm linear regression analysis logistic regression analysis loss function machine learning Markov random field mathematical parameters methodology pattern recognition physical activity random forest response variable robotics smooth model statistical model support vector machine wavelet analysis 10.3389/fnbot.2013.00021 Frontiers in Neurorobotics 7 DEC Article 21 2020-10-27T11:23:18Z 2020-10-27T11:23:18Z 2013 Article Natekin, A, Knoll, A (2013). Gradient boosting machines, a tutorial. Frontiers in Neurorobotics 7 (DEC) : Article 21. ScholarBank@NUS Repository. https://doi.org/10.3389/fnbot.2013.00021 16625218 https://scholarbank.nus.edu.sg/handle/10635/181584 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Unpaywall 20201031
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	adaboost loss function article classification algorithm conceptual framework custom base learner function decision tree electromyogram electromyograph electrode explanatory variable gradient boosting machine learning human learning algorithm linear regression analysis logistic regression analysis loss function machine learning Markov random field mathematical parameters methodology pattern recognition physical activity random forest response variable robotics smooth model statistical model support vector machine wavelet analysis
spellingShingle	adaboost loss function article classification algorithm conceptual framework custom base learner function decision tree electromyogram electromyograph electrode explanatory variable gradient boosting machine learning human learning algorithm linear regression analysis logistic regression analysis loss function machine learning Markov random field mathematical parameters methodology pattern recognition physical activity random forest response variable robotics smooth model statistical model support vector machine wavelet analysis Natekin, A Knoll, A Gradient boosting machines, a tutorial
description	10.3389/fnbot.2013.00021
author2	MECHANICAL ENGINEERING
author_facet	MECHANICAL ENGINEERING Natekin, A Knoll, A
format	Article
author	Natekin, A Knoll, A
author_sort	Natekin, A
title	Gradient boosting machines, a tutorial
title_short	Gradient boosting machines, a tutorial
title_full	Gradient boosting machines, a tutorial
title_fullStr	Gradient boosting machines, a tutorial
title_full_unstemmed	Gradient boosting machines, a tutorial
title_sort	gradient boosting machines, a tutorial
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/181584
_version_	1800914644352630784

Gradient boosting machines, a tutorial

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