Improving wheat yield prediction through variable selection using Support Vector Regression, Random Forest, and Extreme Gradient Boosting by Juan Carlos Moreno Sánchez, Héctor Gabriel Acosta Mesa, Adrián Trueba Espinosa, Sergio Ruiz Castilla, Farid García Lamont

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Extreme gradient boosting algorithm based urban daily traffic index prediction model: a case study of Beijing, China by Jiancheng Weng, Kai Feng, Yu Fu, Jingjing Wang, Lizeng Mao

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Extreme gradient and boosting algorithm for improved bias-correction and downscaling of CMIP6 GCM data across indian river basin by Chandni Thakur, Venkatesh Budamala, KS Kasiviswanathan, Claudia Teutschbein, Bankaru-Swamy Soundharajan

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Efficient diagnosis of diabetes mellitus using an improved ensemble method by Blessing Oluwatobi Olorunfemi, Adewale Opeoluwa Ogunde, Ahmad Almogren, Abidemi Emmanuel Adeniyi, Sunday Adeola Ajagbe, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Asif Mehmood, Habib Hamam

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The Impact of Environmental Risk on Business Failure: A Fuzzy-Set Qualitative Comparative Analysis Approach with Extreme Gradient Boosting Feature Selection by Mariano Romero Martínez, Pedro Carmona Ibáñez, José Pozuelo Campillo

“…A novel dual-stage methodology was employed, first using Extreme Gradient Boosting (XGBoost) for feature selection to identify the most significant predictors of failure from a dataset of Spanish companies (N = 38,456) using 2022 ORBIS data. …”
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An automatic rice mapping method based on an integrated time-series gradient boosting tree using GF-6 and sentinel-2 images by Xueqin Jiang, Huaqiang Du, Song Gao, Shenghui Fang, Yan Gong, Ning Han, Yirong Wang, Kerui Zheng

“…To address these problems, in this paper, an automatic rice mapping method based on an integrated time-series gradient boosting tree (Auto-ITSGBT) is proposed using GF-6 WFV and Sentinel-2 MSI data. …”
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Prediction Models for Late-Onset Preeclampsia: A Study Based on Logistic Regression, Support Vector Machine, and Extreme Gradient Boosting Models by Yangyang Zhang, Xunke Gu, Nan Yang, Yuting Xue, Lijuan Ma, Yongqing Wang, Hua Zhang, Keke Jia

“…Notably, the logistic regression and extreme gradient boosting models exhibited high negative predictive values of 99.3%, underscoring their effectiveness in accurately identifying pregnant women less likely to develop late-onset preeclampsia. …”
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FETAL HEALTH RISK STATUS IDENTIFICATION SYSTEM BASED ON CARDIOTOCOGRAPHY DATA USING EXTREME GRADIENT BOOSTING WITH ISOLATION FOREST AS OUTLIER DETECTION by Firda Yunita Sari, Dian Candra Rini Novitasari, Abdulloh Hamid, Dina Zatusiva Haq

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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…This study aimed to develop an accurate and reliable model for predicting suspended sediment load (SL) in river systems, which is crucial for water resource management and environmental protection. While Xtreme Gradient Boosting (XGB), a powerful ensemble machine learning (ML) model, has been employed in previous studies, the novelty of this research lies in the introduction of a hybrid approach that synergistically combines XGB with the bio-inspired Marine Predators Algorithm (XGB-MPA) to estimate SL in the Yeşilirmak River (Turkey). …”
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Self compacting concrete with recycled aggregate compressive strength prediction based on gradient boosting regression tree with Bayesian optimization hybrid model by Emad A. Abood, Zainab Abdulrdha Thoeny, Noralhuda M. Azize, Hamza Imran, Viroon Kamchoom, Kennedy C. Onyelowe, Krishna Prakash Arunachalam

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Retraction Note: Influence of grey wolf optimization feature selection on gradient boosting machine learning techniques for accurate detection of liver tumor by Malik Jawarneh, José Luis Arias-Gonzáles, Dattatray P. Gandhmal, Rami Qays Malik, Kantilal Pitambar Rane, Batyrkhan Omarov, Cosmena Mahapatra, Mohammad Shabaz

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Machine learning-based evaluation of performance of silicon nitride waveguide fabrication: Gradient-boosted forests for predicting propagation and bend excess losses by Hinum-Wagner Jakob Wilhelm, Hoermann Samuel Marko, Feigl Gandolf, Schmidt Christoph, Kraft Jochen, Bergmann Alexander

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Unveiling the optimal factor model in Pakistan: a machine learning approach using support vector regression and extreme gradient boosting algorithms by Rizwan Ullah, Muhammad Naveed Jan, Muhammad Tahir

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Enhanced extreme gradient boosting based algorithm for mobility management of autonomous vehicles from sub 6 GHz to mmWave networks by Saad Ijaz Majid, Sohaib Ijaz Majid, Shahid Khan, Salah Ud-Din Khan, Haider Ali, Anwar Ali, Neelam Gohar, Slawomir Koziel

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Ensemble machine learning-based pre-trained annotation approach for scRNA-seq data using gradient boosting with genetic optimizer by Osama Elnahas, Waleed M. Ead, Yushan Qiu, Jian Lu

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A comparative performance study on the development of hybrid extreme gradient boosting models for predicting rock layer subsidence in subsea gold mine by Weijun Liu, Zhixiang Liu, Meng Wang, Shuangxia Zhang

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Comparison of light gradient boosting and logistic regression for interactomic hub genes in Porphyromonas gingivalis and Fusobacterium nucleatum-induced periodontitis with Alzheime... by Pradeep Kumar Yadalam, Shubhangini Chatterjee, Prabhu Manickam Natarajan, Carlos M. Ardila, Carlos M. Ardila

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Detection of Depressive Symptoms in College Students Using Multimodal Passive Sensing Data and Light Gradient Boosting Machine: Longitudinal Pilot Study by Jessica L Borelli, Yuning Wang, Frances Haofei Li, Lyric N Russo, Marta Tironi, Ken Yamashita, Elayne Zhou, Jocelyn Lai, Brenda Nguyen, Iman Azimi, Christopher Marcotullio, Sina Labbaf, Salar Jafarlou, Nikil Dutt, Amir Rahmani

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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

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Pareto-driven gradient-boosted Bayesian optimization for multi-objective inverse design of Aerogel-cement-EPS panels in small-sample regimes by Lu Lu, Anming Bai, Haodong Wang, Wenjia Xi, Shan Yun, Shangbing Gao, Mingming Wang, Xinguo Sun

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