Výsledky vyhľadávania - xgboost（extreme gradient boosting） algorithm~

Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms.

Autori: Eroğlu, Mehmet Turgut, Ali Osman Küçük, Mürsel a ďalší

Zdroj: Veterinary Medicine & Science. Jul2025, Vol. 11 Issue 4, p1-8. 8p.

Predmet: Machine learning, Animal breeding, Animal health, Artificial selection of animals, Random forest algorithms

Aircraft flight quality evaluation based on grey correlation analysis and XGBoost

Autori: SUN Baosong SHI Zhiguo PAN Xinlong a ďalší

Zdroj: Hangkong gongcheng jinzhan, Vol 16, Iss 4, Pp 74-81 (2025)

Predmety: grey correlation analysis method, quality assessment model, xgboost（extreme gradient boosting） algorithm, machine learning, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Popis súboru: electronic resource

Relation: http://hkgcjz.cnjournals.com/hkgcjz/article/abstract/2024060; https://doaj.org/toc/1674-8190

Prístupová URL adresa: https://doaj.org/article/61892dc1cab14f76a6bc30ce6a687031

IDSSCNN-XgBoost: Improved Dual-Stream Shallow Convolutional Neural Network Based on Extreme Gradient Boosting Algorithm for Micro Expression Recognition.

Autori: Ahmad, Adnan Li, Zhao Tariq, Irfan a ďalší

Zdroj: Computers, Materials & Continua; 2025, Vol. 82 Issue 1, p729-749, 21p

Predmety: ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, BOOSTING algorithms, SCIENCE databases, DATABASES

Predicting Live Weight for Female Rabbits of Meat Crosses From Body Measurements Using LightGBM, XGBoost and Support Vector Machine Algorithms.

Autori: Önder, Hasan Tirink, Cem Yakubets, Taras a ďalší

Zdroj: Veterinary Medicine & Science. Jan2025, Vol. 11 Issue 1, p1-12. 12p.

Predmet: Support vector machines, Standard deviations, Chest (Anatomy), Mathematical models, Animal welfare

Accurate Biometric Palm Print Recognition Using ResNet50 algorithm Over X Gradient Boosting Algorithm.

Autori: Kumar, H. Kishore Kumar, S. Ashok

Zdroj: E3S Web of Conferences; 7/2/2023, Vol. 399, p1-8, 8p

Comparing the performance of xgboost, Gradient Boosting and GBLUP models under different genomic prediction scenarios.

Autori: Ghafouri-Kesbi, Farhad

Zdroj: Journal of Livestock Science & Technologies (JLST); 2024, Vol. 12 Issue 1, p31-37, 7p

Predmety: GENOMES, BOOSTING algorithms, PARALLEL computers, PARALLEL programming, SINGLE nucleotide polymorphisms, COMPUTERS, SUPPLY & demand, DATA analysis, GENOTYPES

Assessing the predictive value of morphological traits on primary lifestyle of birds through the extreme gradient boosting algorithm.

Autori: Madrigal-Roca, Luis Javier

Zdroj: PLoS ONE; 1/5/2024, Vol. 19 Issue 1, p1-18, 18p

Predmety: MACHINE learning, BOOSTING algorithms, IMPORTANT bird areas, BIRD ecology, BIRD populations, ECOLOGICAL niche, ECOLOGICAL models

Rapid‐Mapping Maximum Water Depth Map of Urban Flood Using a Highly Adaptable Machine Learning Based Model.

Autori: Li, Jingru Pan, Guiying Chen, Yangyu a ďalší

Zdroj: Journal of Flood Risk Management; Sep2025, Vol. 18 Issue 3, p1-18, 18p

Predmety: MACHINE learning, WATER depth, CARTOGRAPHY, RANDOM forest algorithms, BOOSTING algorithms, FLOOD risk

Geografický termín: CHINA, SHENZHEN (Guangdong Sheng, China : East)

A machine learning-based fall-risk score for severity of fall-related adverse outcomes in community older adults.

Autori: Chen, Huihe Ling, Tongsheng Huang, Lanhui a ďalší

Zdroj: BMC Geriatrics; 9/26/2025, Vol. 25 Issue 1, p1-11, 11p

Predmety: MACHINE learning, OLDER people, HEALTH risk assessment, RISK assessment, BOOSTING algorithms

An AI-driven Predictive Model for Pancreatic Cancer Patients Using Extreme Gradient Boosting

Autori: Aditya Chakraborty Chris P. Tsokos

Zdroj: Journal of Statistical Theory and Applications (JSTA), Vol 22, Iss 4, Pp 262-282 (2023)

Predmety: 0301 basic medicine, Pancreatic Cancer, 03 medical and health sciences, 0202 electrical engineering, electronic engineering, information engineering, Boosted Regression Trees, Pancreatic Risk Factors, 02 engineering and technology, Extreme Gradient Boosting, Probabilities. Mathematical statistics, Grid Search Mechanism, QA273-280, 3. Good health

Prístupová URL adresa: https://doaj.org/article/41e7c4c7bf57462f92667c2e2e3bc93c

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm.

Autori: Tyagi, Pankaj Sharma, Anju Semwal, Rahul a ďalší

Zdroj: Journal of Biomolecular Structure & Dynamics; 2024, Vol. 42 Issue 20, p10727-10738, 12p

XGBoost Machine Learning Algorithm for Prediction of Outcome in Aneurysmal Subarachnoid Hemorrhage

Autori: Ruoran Wang Jing Zhang Baoyin Shan a ďalší

Zdroj: Neuropsychiatr Dis Treat
Neuropsychiatric Disease and Treatment, Vol Volume 18, Pp 659-667 (2022)

Predmety: Neuropsychiatric Disease and Treatment, Neurosciences. Biological psychiatry. Neuropsychiatry, artificial intelligence, 3. Good health, 03 medical and health sciences, machine learning, 0302 clinical medicine, extreme gradient boosting, aneurysmal subarachnoid hemorrhage, prognosis, Neurology. Diseases of the nervous system, RC346-429, RC321-571, Original Research

Popis súboru: text/html

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/35378822
https://doaj.org/article/ff2a6ac6bdbf473b881bc0b0b387fdba
https://www.dovepress.com/xgboost-machine-learning-algorithm-for-prediction-of-outcome-in-aneury-peer-reviewed-fulltext-article-NDT

A novel prediction method for coalbed methane production capacity combined extreme gradient boosting with bayesian optimization.

Autori: Du, Shuyi Wang, Meizhu Yang, Jiaosheng a ďalší

Zdroj: Computational Geosciences; Oct2024, Vol. 28 Issue 5, p781-790, 10p

XGBoost Machine Learning Algorithm for Prediction of Outcome in Aneurysmal Subarachnoid Hemorrhage

Autori: Wang R Zhang J Shan B a ďalší

Zdroj: Neuropsychiatric Disease and Treatment, Vol 18, Pp 659-667 (2022)

Predmety: machine learning, artificial intelligence, extreme gradient boosting, aneurysmal subarachnoid hemorrhage, prognosis, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429

Popis súboru: electronic resource

Relation: https://www.dovepress.com/xgboost-machine-learning-algorithm-for-prediction-of-outcome-in-aneury-peer-reviewed-fulltext-article-NDT; https://doaj.org/toc/1178-2021

Prístupová URL adresa: https://doaj.org/article/ff2a6ac6bdbf473b881bc0b0b387fdba

Performance-oriented road structure and material design method based on enhanced XGBoost algorithm.

Autori: Li, Jiale Zhang, Zhishuai Wang, Xuefei

Zdroj: International Journal of Pavement Engineering; Dec2024, Vol. 25 Issue 1, p1-15, 15p

Predmety: PARTICLE swarm optimization, ROAD construction, BOOSTING algorithms, CONSTRUCTION management, PARETO optimum, PAVEMENTS

An AI-driven Predictive Model for Pancreatic Cancer Patients Using Extreme Gradient Boosting.

Autori: Chakraborty, Aditya Tsokos, Chris P.

Zdroj: Journal of Statistical Theory & Applications; Dec2023, Vol. 22 Issue 4, p262-282, 21p

Predmety: PANCREATIC cancer diagnosis, CARCINOGENICITY, STANDARD deviations, CANCER-related mortality, BODY mass index

Protein structural domain-disease association prediction based on heterogeneous networks.

Autori: Zhang, Jingpu Deng, Lianping Deng, Lei

Zdroj: BMC Genomics; 4/10/2025, Vol. 26 Issue 1, p1-14, 14p

Predmety: MACHINE learning, FEATURE extraction, ARTIFICIAL intelligence, PROTEIN structure, IMAGE processing, CLASSIFICATION algorithms

Machine Learning Algorithms for Identifying Dependencies in OT Protocols.

Autori: Smolarczyk, Milosz Pawluk, Jakub Kotyla, Alicja a ďalší

Zdroj: Energies (19961073); May2023, Vol. 16 Issue 10, p4056, 24p

Predmety: MACHINE learning, DECISION trees, DIFFERENTIAL equations, PHYSICS laboratories, TCP/IP, ALGORITHMS, INTRUSION detection systems (Computer security), BOOSTING algorithms

Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka.

Autori: Rathnayake, Namal Rathnayake, Upaka Dang, Tuan Linh a ďalší

Zdroj: PLoS ONE; 4/26/2023, Vol. 18 Issue 4, p1-21, 21p

Predmety: LAND cover, SOFT computing, BOOSTING algorithms, STANDARD deviations, METEOROLOGICAL precipitation, STREAMFLOW

Geografický termín: SRI Lanka

XGBoost algorithm for predicting heat transfer coefficient of saturated flow boiling in mini/micro-channels.

Autori: Noh, Hyeonseok Kim, Jihyeok Lee, Seunghyun a ďalší

Zdroj: International Journal of Heat & Mass Transfer. Mar2026:Part 2, Vol. 256, pN.PAG-N.PAG. 1p.

Predmety: *HEAT transfer coefficient, *MACHINE learning, *ENSEMBLE learning, *OPTIMIZATION algorithms, *MICROFLUIDICS, *EBULLITION