A neural network boosting regression model based on XGBoost-Reference-Cited by-同舟云学术

A neural network boosting regression model based on XGBoost

Published:2022-08 Issue: Volume:125 Page:109067
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Dong Jianwei,Chen Yumin,Yao Bingyu^ORCID,Zhang Xiao,Zeng Nianfeng

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Software

Reference31 articles.

1. Learning boolean formulae or finite automata is as hard as factoring;Kearns;Technical Report TR-14-88 Harvard University Aikem Computation Laboratory,1988

2. Cryptographic limitations on learning boolean formulae and finite automata;Kearns;Journal of the ACM (JACM),1994

3. A decision-theoretic generalization of on-line learning and an application to boosting;Freund;J. Comput. System Sci.,1997

4. Greedy function approximation: a gradient boosting machine;Friedman;Ann. Statist.,2001

5. Xgboost: A scalable tree boosting system;Chen,2016

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