Search Results - Boosting Machine Learning Algorithms

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  1. 1

    The evolution of boosting algorithms. From machine learning to statistical modelling by Mayr, A, Binder, H, Gefeller, O, Schmid, M

    ISSN: 2511-705X, 2511-705X
    Published: Germany 2014
    “… This review article attempts to highlight the evolution of boosting algorithms from machine learning to statistical modelling…”
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    Journal Article
  2. 2

    A Novel Scheme for Mapping of MVT-Type Pb–Zn Prospectivity: LightGBM, a Highly Efficient Gradient Boosting Decision Tree Machine Learning Algorithm by Hajihosseinlou, Mahsa, Maghsoudi, Abbas, Ghezelbash, Reza

    ISSN: 1520-7439, 1573-8981
    Published: New York Springer US 01.12.2023
    “…The gradient boosting decision tree is a well-known machine learning algorithm. Despite numerous advancements in its application, its efficiency still needs to be improved for large feature dimensions and data capacities…”
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    Journal Article
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    Predicting compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement using boosting machine learning algorithms by Rathakrishnan, Vimal, Bt. Beddu, Salmia, Ahmed, Ali Najah

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 09.06.2022
    Published in Scientific reports (09.06.2022)
    “… In this research, compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement is predicted using boosting machine learning (BML…”
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    Journal Article
  5. 5

    Flood susceptibility mapping using machine learning boosting algorithms techniques in Idukki district of Kerala India by Saravanan, Subbarayan, Abijith, Devanantham, Reddy, Nagireddy Masthan, KSS, Parthasarathy, Janardhanam, Niraimathi, Sathiyamurthi, Subbarayan, Sivakumar, Vivek

    ISSN: 2212-0955, 2212-0955
    Published: Elsevier B.V 01.05.2023
    Published in Urban climate (01.05.2023)
    “…) data, Geographic Information System (GIS), and Machine Learning (ML). In this study, five different ML models…”
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    Journal Article
  6. 6

    Prediction of combustion, performance, and emission parameters of ethanol powered spark ignition engine using ensemble Least Squares boosting machine learning algorithms by Godwin, D. Jesu, Varuvel, Edwin Geo, Martin, M. Leenus Jesu

    ISSN: 0959-6526, 1879-1786
    Published: Elsevier Ltd 01.10.2023
    Published in Journal of cleaner production (01.10.2023)
    “… Input for training and evaluating machine learning algorithms, such as Artificial Neural Networks (ANN…”
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    Journal Article
  7. 7

    Exponential smoothing method against the gradient boosting machine learning algorithm-based model for materials forecasting to minimize inventory by Sathish, T., SaiKumar, Divity, Patil, Shashwath, Saravanan, R., Giri, Jayant, Aly, Ayman A.

    ISSN: 2158-3226, 2158-3226
    Published: Melville American Institute of Physics 01.06.2024
    Published in AIP advances (01.06.2024)
    “…) and Gradient Boosting (GB), within the framework of materials forecasting aimed at inventory minimization…”
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    Journal Article
  8. 8

    Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Alkhayyal, Maram A., Mostafa, Almetwally M.

    ISSN: 1424-8220, 1424-8220
    Published: Switzerland MDPI AG 30.06.2025
    Published in Sensors (Basel, Switzerland) (30.06.2025)
    “… Previous studies have employed various Machine Learning (ML) models for path loss prediction…”
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    Journal Article
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    Application of Gradient Boosting Machine Learning Algorithms to Predict Uniaxial Compressive Strength of Soft Sedimentary Rocks at Thar Coalfield by Shahani, Niaz Muhammad, Kamran, Muhammad, Zheng, Xigui, Liu, Cancan, Guo, Xiaowei

    ISSN: 1687-8086, 1687-8094
    Published: New York Hindawi 2021
    Published in Advances in Civil Engineering (2021)
    “… The application of the gradient boosting machine learning algorithms has been rarely used, especially for UCS prediction, and has performed well, based on the relevant literature of the study…”
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    Journal Article
  11. 11

    Vibration analysis of embedded porous nanobeams under thermal effects using boosting machine learning algorithms and semi-analytical approach by Tariq, Aiman, Uzun, Büşra, Deliktaş, Babür, Yaylı, Mustafa Özgür

    ISSN: 1537-6494, 1537-6532
    Published: Abingdon Taylor & Francis 12.11.2024
    “…This study presents a thermal vibration analysis of functionally graded porous nanobeams using boosting machine learning models and a semi-analytical approach…”
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    Journal Article
  12. 12

    Bagging and boosting machine learning algorithms for modelling sensory perception from simple chemical variables: Wine mouthfeel as a case study by Sáenz-Navajas, María-Pilar, Ferreira, Chelo, Bastian, Susan E.P., Jeffery, David W.

    ISSN: 0950-3293
    Published: Elsevier Ltd 01.08.2025
    Published in Food quality and preference (01.08.2025)
    “…Aiming to predict sensory properties from chemical data, the application of bagging and boosting machine learning (ML…”
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    Journal Article
  13. 13

    Software reuse analytics using integrated random forest and gradient boosting machine learning algorithm by Sandhu, Amandeep Kaur, Batth, Ranbir Singh

    ISSN: 0038-0644, 1097-024X
    Published: Hoboken, USA John Wiley & Sons, Inc 01.04.2021
    Published in Software, practice & experience (01.04.2021)
    “… Machine Learning gives the best results to predicate if the given software component is reusable…”
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  14. 14

    Prediction of Water Saturation from Well Log Data by Machine Learning Algorithms: Boosting and Super Learner by Hadavimoghaddam, Fahimeh, Ostadhassan, Mehdi, Sadri, Mohammad Ali, Bondarenko, Tatiana, Chebyshev, Igor, Semnani, Amir

    ISSN: 2077-1312, 2077-1312
    Published: Basel MDPI AG 01.06.2021
    Published in Journal of marine science and engineering (01.06.2021)
    “… There exist new machine learning (ML) algorithms such as gradient boosting techniques that have shown significant success in other disciplines yet have not been…”
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  15. 15

    A comparative spatial analysis of flood susceptibility mapping using boosting machine learning algorithms in Rathnapura, Sri Lanka by Kurugama, Kumudu Madhawa, Kazama, So, Hiraga, Yusuke, Samarasuriya, Chaminda

    ISSN: 1753-318X, 1753-318X
    Published: Oxford, UK Blackwell Publishing Ltd 01.06.2024
    Published in Journal of flood risk management (01.06.2024)
    “… A spatial database with 595 flood inventory and 13 flood predictors were used to implement five boosting algorithms…”
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  16. 16

    Wildfire Susceptibility Mapping Using Five Boosting Machine Learning Algorithms: The Case Study of the Mediterranean Region of Turkey by Abujayyab, Sohaib K. M., Kassem, Moustafa Moufid, Khan, Ashfak Ahmad, Wazirali, Raniyah, Coşkun, Mücahit, Taşoğlu, Enes, Öztürk, Ahmet, Toprak, Ferhat

    ISSN: 1687-8086, 1687-8094
    Published: New York Hindawi 2022
    Published in Advances in Civil Engineering (2022)
    “… Modern machine learning techniques have become popular in developing very accurate and precise susceptibility maps of various natural disasters to help reduce the occurrence of such calamities…”
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    Ultra-high performance concrete compressive strength prediction using machine learning boosting algorithms by Brahmeswari, L. Chandana, Rao, B. D. V. Chandra Mohan

    ISSN: 1563-0854, 2522-011X
    Published: Cham Springer International Publishing 01.12.2025
    “… This study examines how well two sophisticated machine learning boosting models, Gradient…”
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    Predicting and analyzing flood susceptibility using boosting-based ensemble machine learning algorithms with SHapley Additive exPlanations by Aydin, Halit Enes, Iban, Muzaffer Can

    ISSN: 0921-030X, 1573-0840
    Published: Dordrecht Springer Netherlands 01.04.2023
    Published in Natural hazards (Dordrecht) (01.04.2023)
    “… of Türkiye using tree-based machine learning (ML) classifiers. This study seeks to analyze the predictive performance of Natural Gradient Boosting Machines (NGBoost…”
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  20. 20

    Hourly PM2.5 concentration multi-step forecasting method based on extreme learning machine, boosting algorithm and error correction model by Yin, Shi, Liu, Hui, Duan, Zhu

    ISSN: 1051-2004, 1095-4333
    Published: Elsevier Inc 01.11.2021
    Published in Digital signal processing (01.11.2021)
    “…2.5 concentration is proposed. Two boosting algorithms, Modified AdaBoost.RT and Gradient Boosting, are used to enhance the extreme learning machine (ELM…”
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    Journal Article