A new ensemble learning method stratified sampling blending optimizes conventional blending and improves prediction performance

Authors

Mengjin Zhu (ORCID: https://orcid.org/0000-0001-8931-5022)
Mengke Yang (ORCID: https://orcid.org/0000-0002-4671-4848)
Zhaoxuan Che (ORCID: https://orcid.org/0009-0009-5447-4774)
Xiangyu Dai
Pingping Han (ORCID: https://orcid.org/0000-0001-8257-4312)
Jiakun Qiao (ORCID: https://orcid.org/0009-0001-3591-2531)
Fangjun Xu
Na Miao

Institutions

Huazhong Agricultural University (CN)
Center of Hubei Cooperative Innovation for Emissions Trading System (CN)

Publication Details

Journal: Bioinformatics Advances
Published: 2024-12-26
DOI: https://doi.org/10.1093/bioadv/vbaf002
Citations: 3
Primary Topic: Face and Expression Recognition
Type: article
Field-Weighted Citation Impact: 0.75

Funders

National Natural Science Foundation of China
Earmarked Fund for China Agriculture Research System
National Key Research and Development Program of China

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article

A new ensemble learning method stratified sampling blending optimizes conventional blending and improves prediction performance

Mengjin Zhu, Mengke Yang, Zhaoxuan Che, Xiangyu Dai et al.

Dec 26, 2024

3 citations

Bioinformatics Advances

Face and Expression Recognition

0.75

article

A new ensemble learning method stratified sampling blending optimizes conventional blending and improves prediction performance

Mengjin Zhu, Mengke Yang, Zhaoxuan Che, Xiangyu Dai, Pingping Han, Jiakun Qiao, Fangjun Xu, Na Miao

December 26, 2024article en

3 citations

Abstract

No abstract available for this paper.

Bioinformatics AdvancesVol. 5(1)

Huazhong Agricultural University (CN), Center of Hubei Cooperative Innovation for Emissions Trading System (CN)

National Natural Science Foundation of China, Earmarked Fund for China Agriculture Research System, National Key Research and Development Program of China

Openalex Percentile: Top 26%

Face and Expression Recognition

0.75

DOI Open Access PDF OpenAlex

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