Suchergebnisse - "gradient boosting algorithms"

PlantLncBoost: key features for plant lncRNA identification and significant improvement in accuracy and generalization

Autoren: Tian, Xue-Chan Nie, Shuai Domingues, Douglas et al.

Quelle: New Phytologist. 247(3):1538-1549

Schlagwörter: feature selection, Fourier transform, gradient boosting algorithms, long noncoding RNAs (lncRNAs), model selection, ORF coverage

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-240920
https://doi.org/10.1111/nph.70211

Analysis and development of risk prediction models for chronic opioid use after surgery: a cohort study using the nationwide database

Autoren: Jonghae Kim Hyun-Lim Yang Eugene Kim et al.

Quelle: Korean Journal of Anesthesiology, Vol 78, Iss 5, Pp 429-442 (2025)

Schlagwörter: dependence, opioid, gradient boosting algorithms, machine learning, postoperative period, prediction methods, machine, surgical procedures, operative, Anesthesiology, RD78.3-87.3

Dateibeschreibung: electronic resource

Relation: http://ekja.org/upload/pdf/kja-24831.pdf; https://doaj.org/toc/2005-6419; https://doaj.org/toc/2005-7563

Zugangs-URL: https://doaj.org/article/52378890d3e74f4f9ba94ad2ab5a4bc7

Meta Learning Strategies for Comparative and Efficient Adaptation to Financial Datasets

Autoren: Kubra Noor Ubaida Fatima

Quelle: IEEE Access, Vol 13, Pp 24158-24170 (2025)

Schlagwörter: gradient boosting algorithms, machine learning in finance, Meta-learning techniques, advanced feature selection, dynamic predictive models, financial market prediction, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Zugangs-URL: https://doaj.org/article/bc59e6f80d0b47268029a9e7f45cb179

Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm

Autoren: Dongjie Guan Yitong Shi Lilei Zhou et al.

Quelle: Remote Sensing, Vol 17, Iss 14, p 2383 (2025)

Schlagwörter: carbon emission forecasting, county level, gradient boosting algorithms, spatiotemporal patterns, SHAP interpretation, Science

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2072-4292/17/14/2383; https://doaj.org/toc/2072-4292

Zugangs-URL: https://doaj.org/article/4acc578eb0134741bd02b2a727f372df

Comparative Analysis of Gradient-Boosting Ensembles for Estimation of Compressive Strength of Quaternary Blend Concrete

Autoren: Ismail B. Mustapha Muyideen Abdulkareem Taha M. Jassam et al.

Quelle: International Journal of Concrete Structures and Materials, Vol 18, Iss 1, Pp 1-24 (2024)

Schlagwörter: Compressive strength, Quaternary blend concrete, Gradient-boosting algorithms, Ensemble machine learning, Systems of building construction. Including fireproof construction, concrete construction, TH1000-1725

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2234-1315

Zugangs-URL: https://doaj.org/article/c79848ea92844d20bb84a6f50ba1f103

In-silico Mutajenite Tahmini için Hibrit Metasezgisel Tabanlı Özellik Seçimi Çerçevesi

Autoren: Yılmaz, Özlem Gumustas, Enis Çakmak Pehlivanlı, Ayça

Quelle: Volume: 7, Issue: 2116-128
Journal of Intelligent Systems: Theory and Applications
Zeki Sistemler Teori ve Uygulamaları Dergisi

Schlagwörter: Makine Öğrenme (Diğer), Machine Learning, Feature Selection, Metaheuristics, Gradient Boosting Algorithms, Mutagenicity Prediction, In-Silico Modelling, Veri Yönetimi ve Veri Bilimi (Diğer), Makine Öğrenmesi, Özellik Seçimi, Metasezgisel, Gradyan Boosting Algoritmaları, Mutajenite Tahmini, In-Silico Modelleme, Machine Learning (Other), Data Management and Data Science (Other)

Dateibeschreibung: application/pdf

Zugangs-URL: https://dergipark.org.tr/tr/pub/jista/issue/87334/1468153

Fraud detection under the unbalanced class based on gradient boosting

Autoren: Raya Alothman Hassanein Ali Talib Mazin S. Mohammed

Quelle: Eastern-European Journal of Enterprise Technologies; Vol. 2 No. 2 (116) (2022): Information technology. Industry control systems; 6-12
Eastern-European Journal of Enterprise Technologies; Том 2 № 2 (116) (2022): Інформаційні технології. Системи управління в промисловості; 6-12

Schlagwörter: machine learning, gradient boosting algorithms, моделювання кредитного шахрайства, алгоритми підвищення градієнта, unbalanced data, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, credit fraud modeling, машинне навчання, незбалансовані дані, 02 engineering and technology

Dateibeschreibung: application/pdf

Zugangs-URL: http://journals.uran.ua/eejet/article/view/254922

Design of an Intrusion Detection Model for IoT-Enabled Smart Home

Autoren: Deepti Rani Nasib Singh Gill Preeti Gulia et al.

Quelle: IEEE Access, Vol 11, Pp 52509-52526 (2023)

Schlagwörter: Machine learning classification algorithms, ensemble classifiers, gradient boosting algorithms, light gradient boosting machines (LGBM), and intrusion detection systems (IDS), Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/10124866/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/a1a91a94b0ba488e8a2e6fd531fda6d0

Exploring the PV Power Forecasting at Building Façades Using Gradient Boosting Methods

Autoren: Polo Martínez, Jesús Martín Chivelet, Nuria Alonso Abella, Miguel et al.

Weitere Verfasser: Polo Martínez, Jesús Martín Chivelet, Nuria Alonso Abella, Miguel et al.

Schlagwörter: 728.036, 620.92, BIPV, PV power forecasting, Machine learning, Gradient boosting algorithms, Física de materiales, Física (Química), 2212.03 Energía (Física)

Dateibeschreibung: application/pdf

Relation: info:eu-repo/grantAgreement/MICINN/PID2021-124910OB-C3; https://hdl.handle.net/20.500.14352/103514

Verfügbarkeit: https://hdl.handle.net/20.500.14352/103514
https://doi.org/10.3390/en16031495

Classification and Prediction of Wafer Yield Using Gradient Boosting Algorithms:A Focus on Lithography Inline Parameters

Autoren: Islam, Mohammed Nizamul Islam, Md Tarekul Dhali, Maruf A. et al.

Weitere Verfasser: Islam, Mohammed Nizamul Islam, Md Tarekul Dhali, Maruf A. et al.

Quelle: Islam, M N, Islam, M T & Dhali, M A 2025, Classification and Prediction of Wafer Yield Using Gradient Boosting Algorithms : A Focus on Lithography Inline Parameters. in A Abdelgawad, A Jamil & A A Hameed (eds), 2025 IEEE 4th International Conference on Computing and Machine Intelligence, ICMI 2025 - Proceedings. 2025 IEEE 4th International Conference on Computing and Machine Intelligence, ICMI 2025 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 4th IEEE International Conference on Computing and Machine Intelligence, ICMI 2025, Michigan, United States, 05/04/2025. https://doi.org/10.1109/ICMI65310.2025.11141195

Schlagwörter: Gradient Boosting Algorithms, GridSearchCV, Hyperparameter tuning, LightGBM, Machine Learning in the semiconductor industry, Mean Absolute Error (MAE), Mean Squared Error (MSE), Photolithography, R-squared value, Semiconductor yield analysis

Relation: info:eu-repo/semantics/altIdentifier/hdl/https://hdl.handle.net/11370/5aac0283-d516-4017-80bc-777cbe95d0d4; info:eu-repo/semantics/altIdentifier/isbn/9798331509132; urn:ISBN:9798331509132

Verfügbarkeit: https://hdl.handle.net/11370/5aac0283-d516-4017-80bc-777cbe95d0d4
https://research.rug.nl/en/publications/5aac0283-d516-4017-80bc-777cbe95d0d4
https://doi.org/10.1109/ICMI65310.2025.11141195
https://www.scopus.com/pages/publications/105017004505

Predicting Airbnb Prices in Dubai using Machine Learning

Autoren: Altamimi, Hamad Younus

Quelle: Theses

Schlagwörter: Airbnb Dubai, Ensemble modeling, Gradient boosting algorithms, Hyperparameter tuning, Random forest ensemble technique, Rental prices prediction

Dateibeschreibung: application/pdf

Relation: https://repository.rit.edu/theses/12033; https://repository.rit.edu/context/theses/article/13167/viewcontent/HAltamimiThesis1_2025.pdf

Verfügbarkeit: https://repository.rit.edu/theses/12033
https://repository.rit.edu/context/theses/article/13167/viewcontent/HAltamimiThesis1_2025.pdf

Fraud Detection Under the Unbalanced Class Based on Gradient Boosting

Autoren: Alothman, R. (Raya) Talib, H. A. (Hassanein) Mohammed, M. S. (Mazin)

Quelle: Eastern-European Journal of Enterprise Technologies

Schlagwörter: Indonesia, машинне навчання, machine learning, моделювання кредитного шахрайства, незбалансовані дані, алгоритми підвищення градієнта, credit fraud modeling, unbalanced data, gradient boosting algorithms

Dateibeschreibung: application/pdf

Verfügbarkeit: https://www.neliti.com/publications/609370/fraud-detection-under-the-unbalanced-class-based-on-gradient-boosting

Comparative Analysis of ML based Gradient Boosting Algorithms: XGBoost, CatBoost, and LightGBM

Autoren: Bhargava Kumar Tejaswini Kumar

Schlagwörter: Gradient Boosting Algorithms, XGBoost, CatBoost, LightGBM, Predictive Modeling

Relation: https://zenodo.org/records/12666689; oai:zenodo.org:12666689; https://doi.org/10.5281/zenodo.12666689

Verfügbarkeit: https://doi.org/10.5281/zenodo.12666689
https://zenodo.org/records/12666689

Machine Learning-Based Lightning Localization Algorithm Using Lightning-Induced Voltages on Transmission Lines

Autoren: Karami, Hamidreza Mostajabi, Amirhossein Azadifar, Mohammad et al.

Weitere Verfasser: Karami, Hamidreza Mostajabi, Amirhossein Azadifar, Mohammad et al.

Quelle: ISSN: 0018-9375 ; IEEE Transactions on Electromagnetic Compatibility ; https://hal.archives-ouvertes.fr/hal-03589923 ; IEEE Transactions on Electromagnetic Compatibility, Institute of Electrical and Electronics Engineers, 2020, 62 (6), pp.2512-2519. ⟨10.1109/TEMC.2020.2978429⟩.

Schlagwörter: Lightning Localization, Machine Learning, Transients on Transmission Lines, Gradient Boosting Algorithms, [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]

Relation: info:eu-repo/grantAgreement//737033/EU/Laser Lightning Rod/LLR; hal-03589923; https://hal.archives-ouvertes.fr/hal-03589923; https://hal.archives-ouvertes.fr/hal-03589923/document; https://hal.archives-ouvertes.fr/hal-03589923/file/3.%20Source_localization_Final_Version.pdf

Verfügbarkeit: https://hal.archives-ouvertes.fr/hal-03589923
https://hal.archives-ouvertes.fr/hal-03589923/document
https://hal.archives-ouvertes.fr/hal-03589923/file/3.%20Source_localization_Final_Version.pdf
https://doi.org/10.1109/TEMC.2020.2978429

Vývoj a evaluace skóringových modelů pro bankovní retailový sektor ; Development and Evaluation of Scoring Models for the Banking Retail Sector

Autoren: Brachtlová, Gabriela Witzany, Jiří Jouda, Jan

Weitere Verfasser: Brachtlová, Gabriela Witzany, Jiří Jouda, Jan

Schlagwörter: rating, validation, calibration, credit risk management, scoring model, neural networks, machine learning, credit risk, scoring, Random Forest, gradient boosting algorithms, logistic regression, decision trees, LightGBM, validace, logistická regrese, rozhodovací stromy, gradient boosting algoritmy, kreditní riziko, řízení kreditního rizika, skóringový model, kalibrace, skóring, strojové učení, neuronové sítě

Dateibeschreibung: application/pdf

Relation: https://vskp.vse.cz/eid/98052

Verfügbarkeit: https://vskp.vse.cz/eid/98052

Application of machine-learning algorithms for tephrochronology: a case study of Plio-Quaternary volcanic fields in the South Aegean Active Volcanic Arc

Autoren: Uslular, Göksu Kıyıkçı, Fatih Karaarslan, Enis et al.

Weitere Verfasser: Uslular, Göksu Kıyıkçı, Fatih Karaarslan, Enis et al.

Schlagwörter: Tephrochronology, Machine-learning, Gradient boosting algorithms, Imbalanced data, South Aegean Active Volcanic Arc

Dateibeschreibung: application/pdf

Relation: EARTH SCIENCE INFORMATICS; Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı; https://hdl.handle.net/20.500.12809/9909

Verfügbarkeit: https://hdl.handle.net/20.500.12809/9909
https://doi.org/10.1007/s12145-022-00797-5

Automation of price prediction using machine learning in a large furniture company

Autoren: Ghorbanali, Mojtaba

Schlagwörter: Price Prediction, Machine learning, Regression analysis, Gradient boosting algorithms, LightGBM, XGBoost, Computer Sciences, Datavetenskap (datalogi)

Dateibeschreibung: application/pdf

Verfügbarkeit: http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-58921

Tree-Based Modeling Methods to Predict Nitrate Exceedances in the Ogallala Aquifer in Texas

Autoren: Venkatesh Uddameri Ana Silva Sreeram Singaraju et al.

Quelle: Water
Volume 12
Issue 4

Schlagwörter: random forests, Ogallala Aquifer, 2. Zero hunger, gradient boosting algorithms, 0207 environmental engineering, MARS, 02 engineering and technology, 15. Life on land, water quality, 01 natural sciences, 6. Clean water, machine learning, nitrate, 13. Climate action, CART, aquifer vulnerability, 0105 earth and related environmental sciences

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.mdpi.com/2073-4441/12/4/1023/pdf
https://www.mdpi.com/2073-4441/12/4/1023
https://www.mdpi.com/2073-4441/12/4/1023/pdf

Tree-based modeling methods to predict nitrate exceedances in the Ogallala aquifer in Texas

Autoren: Uddameri, Venkatesh Silva, Ana Luiza Bessa Singaraju, Sreeram et al.

Schlagwörter: Aquifer vulnerability, CART, Gradient boosting algorithms, Machine learning, MARS, Nitrate, Ogallala aquifer, Random forests, Water quality, geo, envir

Relation: https://hdl.handle.net/2346/92199

Verfügbarkeit: https://hdl.handle.net/2346/92199

Machine learning classification of internet worms and ransomware attacks and effect of BGP feature properties

Autoren: Takhar, Hardeep Kaur

Schlagwörter: Communication networks, Cybersecurity, Intrusion Detection, Malware, Worms, Ransomware attacks, Anomaly detection, Border Gateway Protocol, Goodness of fit test, Supervised and unsupervised machine learning, Feature selection, Gradient boosting algorithms

Verfügbarkeit: https://summit.sfu.ca/_flysystem/fedora/2023-05/etd22483.pdf