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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LDA-SCGB: inferring lncRNA-disease associations based on condensed gradient boosting by Chengqiu Dai, Linna Wang, Yingwei Deng, Xuzhu Gao, Jingyu Zhang

“…Next, it classifies unknown lncRNA-disease pairs through the condensed gradient boosting model. The results demonstrated that LDA-SCGB greatly outperformed the other four representative LDA inference methods (SDLDA, LDNFSGB, LDAenDL and LDASR) under 5-fold cross validations on lncRNAs, diseases, and lncRNA-disease pairs on three LDA datasets, which were from lncRNADisease v2.0, MNDR, and lncRNADisease v3.0, respectively. …”
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Predicting lncRNA and disease associations with graph autoencoder and noise robust gradient boosting by Lili Tang, Liangliang Huang, Yi Yuan

“…Next, it was compared with four representative boosting models, i.e., XGBoost, AdaBoost, CatBoost, and LightGBM, under the above three different cross validations. …”
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Research on Sleep Staging Based on Support Vector Machine and Extreme Gradient Boosting Algorithm by Wang Y, Ye S, Xu Z, Chu Y, Zhang J, Yu W

“…Yiwen Wang,1 Shuming Ye,2 Zhi Xu,3 Yonghua Chu,1 Jiarong Zhang,4 Wenke Yu5 1Clinical Medical Engineering Department, The Second Affiliated Hospital, Zhejiang University School of Medicine, HangZhou, ZheJiang, People’s Republic of China; 2Department of Biomedical Engineering, Zhejiang University, HangZhou, ZheJiang, People’s Republic of China; 3China Astronaut Research and Training Center, BeiJing, People’s Republic of China; 4Baidu Inc, BeiJing, People’s Republic of China; 5Radiology Department, ZheJiang Province Qing Chun Hospital, HangZhou, ZheJiang, People’s Republic of ChinaCorrespondence: Yiwen Wang; Shuming Ye, Email karenkaren2010@zju.edu.cn; ysmln@vip.sina.comPurpose: To develop a sleep-staging algorithm based on support vector machine (SVM) and extreme gradient boosting model (XB Boost) and evaluate its performance.Methods: In this study, data features were extracted based on physiological significance, feature dimension reduction was performed through appropriate methods, and XG Boost classifier and SVM were used for classification. …”
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Predictive modeling of longitudinal cracking in CRCP using PSO-tuned gradient boosting machines by Ali Alnaqbi, Ghazi G. Al-Khateeb, Waleed Zeiada

“…Using structural, traffic, and climatic data taken from the Long-Term Pavement Performance (LTPP) database, this study presents a machine learning system based on a gradient boosting machine (GBM) optimized using particle swarm optimization (PSO) to forecast longitudinal cracking. …”
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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 for Tunnelling-Induced Ground Settlement in Multilayered Soils: An Improved Gradient Boosting Approach by Hongbin An, Yangyang Chen, Jingjie Lei, Hanbin Luo, Elton J. Chen

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

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XGBMUT: Predicting the Functional Impact of Missense Mutations Using an Extreme Gradient Boost Classifier by Gabriel Rodrigues Coutinho Pereira, Loiane Mendonça Abrantes Da Conceição, Bárbara de Azevedo Abrahim-Vieira, Carlos Rangel Rodrigues, Lucio Mendes Cabral, Ricardo Limongi França Coelho, Joelma Freire De Mesquita

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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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New Findings From Explainable SYM‐H Forecasting Using Gradient Boosting Machines by Daniel Iong, Yang Chen, Gabor Toth, Shasha Zou, Tuija Pulkkinen, Jiaen Ren, Enrico Camporeale, Tamas Gombosi

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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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Gradient Boosting Feature Selection for Integrated Fault Diagnosis in Series-Compensated Transmission Lines by Rab Nawaz, Abdul Wadood, Khawaja Khalid Mehmood, Syed Basit Ali Bukhari, Hani Albalawi, Aadel Mohammed Alatwi, Muhammad Sajid

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

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Dye-cleaning prediction with a variant of nature-inspired algorithms coupled with extreme gradient boosting by Tiyasha Tiyasha, Chijioke Elijah Onu, Mohamed A. Ismail, Rama Rao Karri, Abdelfattah Amari, Vinay Kumar, Suraj Kumar Bhagat

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Remote Diagnosis and Triaging Model for Skin Cancer Using EfficientNet and Extreme Gradient Boosting by Irfan Ullah Khan, Nida Aslam, Talha Anwar, Sumayh S. Aljameel, Mohib Ullah, Rafiullah Khan, Abdul Rehman, Nadeem Akhtar

“…We used an ensemble-learning framework, consisting of the EfficientNetB3 deep learning model for skin lesion analysis and Extreme Gradient Boosting (XGB) for clinical data. …”
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Integrating Experimental Analysis and Gradient Boosting for the Durability Assessment of Lime-Based Mortar in Acidic Environment by Ali Taheri, Nima Azimi, Daniel V. Oliveira, Joaquim Tinoco, Paulo B. Lourenço

“…In the modeling phase, the extreme gradient boosting (XGBoost) algorithm was deployed to predict the mechanical properties of the lime-based mortar by 1000, 3000, and 5000 h of exposure. …”
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Sistem Personalisasi Pasien Diabetes Berbasis Domain Fitur Menggunakan Algoritma Gradient Boosting Machine by Tutus Praningki, David Thanlian Kurniawan

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A Feasibility Study on Gradient Boosting Regressor for Subsurface Sensor-Based Surface Instability Assessment by Shanelle Aira Rodrigazo, Junhwi Cho, Cherry Rose Godes, Yongseong Kim, Yongjin Kim, Seungjoo Lee, Jaeheum Yeon

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