Investigating the contributors to hit-and-run crashes using gradient boosting decision trees. by Baorui Han, Haibo Huang, Gen Li, Chenming Jiang, Zhen Yang, Zhenjun Zhu

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Privacy-Aware Table Data Generation by Adversarial Gradient Boosting Decision Tree by Shuai Jiang, Naoto Iwata, Sayaka Kamei, Kazi Md. Rokibul Alam, Yasuhiko Morimoto

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Classification of Toraja, Batak and Ambon Languages using Decision Tree and Gradient Boost methods by Bileam Mangalla, Suharyadi Suharyadi

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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

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The nonlinear relationship between built environment and cycling propensity for different travel purposes − based on extreme gradient boosting decision tree by Xiaonan Zhang, Borui Yan, Bo Yao, Jianfeng Xue, Yan Zheng, Chaojun Ren

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Forecast of NOx Emissions for a 660MW Coal-Fired Boiler with Multilayered Gradient Boosting Decision Tree Considering Multiple Operating Modes by Ziwei Wang, Yongzan Zhou, Yukun Zhu, Haiquan Yu, Wei Fan

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Leveraging Azure Automated Machine Learning and CatBoost Gradient Boosting Algorithm for Service Quality Prediction in Hospitality by Avisek Kundu, Seeboli Ghosh Kundu, Santosh Kumar Sahu, Nitesh Dhar Badgayan

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Prognostication of advanced CO2 capture using tunable solvents with an ensemble learning-based decision tree model by Reza Soleimani, Amir Hossein Saeedi Dehaghani, Ziba Behtouei, Hamidreza Farahani, Seyyed Mohsen Hashemi

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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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Integrating explainable artificial intelligence and light gradient boosting machine for glioma grading by Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

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Prediction of Imbalance Prices Through Gradient Boosting Algorithms: An Application to the Greek Balancing Market by Konstantinos Plakas, Nikos Andriopoulos, Dimitrios Papadaskalopoulos, Alexios Birbas, Efthymios Housos, Ioannis Moraitis

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Intelligent method for supporting decision-making on software security using hybrid models by Оксана Сітнікова, Маргарита Мельник, Олена Сирота, Сергій Семенов

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Machine learning-driven prediction of hospital admissions using gradient boosting and GPT-2 by Xingyu Zhang, Hairong Wang, Guan Yu, Wenbin Zhang

“…Structured data included demographics, visit characteristics, vital signs, and medical history, while unstructured data consisted of free-text chief complaints and injury descriptions. A Gradient Boosting Classifier (GBC) was applied to structured data, while a fine-tuned GPT-2 model processed the unstructured text. …”
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Prediction of Sonic Log Values Using a Gradient Boosting Algorithm in the 'AB' Field by Rasif Nahari, Utama Widya, Ardhya Garini Sherly, Fitri Indriani Rista, Pratama Novian Putra Dhea

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Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm by Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

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Incorporation of visible/near-infrared spectroscopy and machine learning models for indirect assessment of grape ripening indicators by Osama Elsherbiny, Salah El-Hendawy, Salah Elsayed, Abdallah Elshawadfy Elwakeel, Abdullah Alebidi, Xianlu Yue, Wael Mohamed Elmessery, Hoda Galal

“…This study proposes an innovative approach combining Visible/Near-Infrared (VIS/NIR) spectroscopy with machine learning techniques—specifically, decision trees (DT) and gradient boosting regression (GBR)—to facilitate a rapid, non-destructive, and cost-effective prediction of key grape ripening indicators such as anthocyanin (An), total acidity (TA), total soluble solids (TSS), and the TSS/TA ratio. …”
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Improving transaction safety via anti-fraud protection based on blockchain by Yong Ren, Yan Ren, Hongwei Tian, Wei Song, Yanhong Yang

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Machine Learning Classification of 3D Intracellular Trafficking Using Custom and Imaris-Derived Motion Features by Oleg Kovtun

“…The approach employs an extended gradient-boosted decision trees classifier trained on an array of synthetic trajectories designed to simulate diffusion behaviors typical of intracellular environments. …”
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