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RESEARCH PAPER · Scientific Reports · 2017

Generating highly accurate prediction hypotheses through collaborative ensemble learning

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42 direct citing works

Generating highly accurate prediction hypotheses through collaborative ensemble learningOriginalGeneralization-Aware Structured Regression towards Balancing Bias and Variance8Spatially Aware Ensemble-Based Learning to Predict Weather-Related Outages in Transmission30Stability of decision trees and logistic regression1Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence292Machine learning-based coronary artery disease diagnosis: A comprehensive review273Classification of the placement success in the undergraduate placement examination according to decision trees with bagging and boosting methods2Application of ensemble RNN deep neural network to the fall detection through IoT environment52Learning from Structured Data: Scalability, Stability and Temporal Awareness0Systematic Review of Supervised Machine Learning Models in Prediction of Medical Conditions6Implementing Ensemble Learning to Predict Temperature Variables of Power Electronics Devices0A Parallel Algorithm for the Detection of Eye Disease27Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery73SEG: Segmentation Evaluation in absence of Ground truth labels5CUDA-BASED PARALLELIZATION OF GRADIENT BOOSTING AND BAGGING ALGORITHM FOR DIAGNOSING DIABETES3Tailored and Impactful Retrofit Guides for Swedish Building Stocks Using Big Data and Explainable Ai0Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning3Impacts of spatial scales and data distribution patterns on geographically weighted machine learning models for the spatial prediction of soil organic carbon2Diverse occupant behaviour and urban building heterogeneity to enhance urban building energy modelling6Predicting ride comfort in high-speed rail using machine learning0

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  1. Generalization-Aware Structured Regression towards Balancing Bias and Variance

    International Joint Conference on Artificial Intelligence · 2018-07-01

    Martin Pavlovski, Fang Zhou, Nino Arsov, Ljupčo Kocarev, Zoran Obradović

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  2. Spatially Aware Ensemble-Based Learning to Predict Weather-Related Outages in Transmission

    Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2019-01-01

    Tatjana Dokic, Martin Pavlovski, Djordje Gligorijevic, Mladen Kezunović, Zoran Obradović

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  3. Stability of decision trees and logistic regression

    arXiv (Cornell University) · 2019-03-03

    Nino Arsov, Martin Pavlovski, Ljupčo Kocarev

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  4. Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence

    Trends in biotechnology · 2019-06-21

    Antoine L. Harfouche, Antoine L. Harfouche, Daniel Jacobson, David Kainer, Jonathon Romero, Antoine H. Harfouche, Antoine H. Harfouche, Giuseppe Scarascia Mugnozza, Menachem Moshelion, Gerald A. Tuskan, Joost J. B. Keurentjes, Arie Altman

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  5. Machine learning-based coronary artery disease diagnosis: A comprehensive review

    Computers in Biology and Medicine · 2019-07-04

    Roohallah Alizadehsani, Moloud Abdar, Mohamad Roshanzamir, Abbas Khosravi, Parham Mohsenzadeh Kebria, Fahime Khozeimeh, Saeid Nahavandi, Nizal Sarrafzadegan, U. Rajendra Acharya

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  6. Classification of the placement success in the undergraduate placement examination according to decision trees with bagging and boosting methods

    Cumhuriyet Science Journal · 2020-03-22

    Tuğba Tuğ Karoğlu, Hayrettin Okut

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  7. Application of ensemble RNN deep neural network to the fall detection through IoT environment

    Alexandria Engineering Journal · 2020-07-24

    Mohammed A. Farsi

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  8. Learning from Structured Data: Scalability, Stability and Temporal Awareness

    TUScholarShare (Temple University) · 2021-01-01

    Martin Pavlovski

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  9. Systematic Review of Supervised Machine Learning Models in Prediction of Medical Conditions

    medRxiv · 2022-04-27

    Branimir Ljubic, Martin Pavlovski, Avrum Gillespie, Daniel J. Rubin, Galen Collier, Zoran Obradović

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  10. Implementing Ensemble Learning to Predict Temperature Variables of Power Electronics Devices

    International Conference on Electronic Packaging Technology (ICEPT) · 2022-08-10

    Weijing Dai, Qi Tang, Zhiqi Wang, Jie Cong, Ke Xue, Shangbing Yang, Dong Lu

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  11. A Parallel Algorithm for the Detection of Eye Disease

    Lecture notes on data engineering and communications technologies · 2023-01-01

    Lesia Mochurad, Rostyslav Panto

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  12. Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery

    The Science of The Total Environment · 2023-02-16

    Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Myoung-Bae Seo, Soo-Mi Choi

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  13. SEG: Segmentation Evaluation in absence of Ground truth labels

    bioRxiv (Cold Spring Harbor Laboratory) · 2023-02-24

    Zachary Sims, Luke Strgar, Dharani Thirumalaisamy, Robert T. Heussner, Guillaume Thibault, Young Hwan Chang

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  14. CUDA-BASED PARALLELIZATION OF GRADIENT BOOSTING AND BAGGING ALGORITHM FOR DIAGNOSING DIABETES

    Computer Systems and Information Technologies · 2023-06-29

    Lesia Mochurad

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  15. Tailored and Impactful Retrofit Guides for Swedish Building Stocks Using Big Data and Explainable Ai

    SSRN Electronic Journal · 2025-01-01

    Santhan Reddy Penaka, Kailun Feng, Thomas Olofsson, Anders Rebbling, Erik Eklund, Weizhuo Lu

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  16. Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning

    Scientific Reports · 2025-07-19

    Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

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  17. Impacts of spatial scales and data distribution patterns on geographically weighted machine learning models for the spatial prediction of soil organic carbon

    Pedosphere · 2025-11-01

    Younghun Lee, Younghun LEE, Hyemin JEONG, Ling DU, Xia Li, Xin Zhang, Byeongwon Lee, Sangchul Lee, Gregory W. McCarty, Sangchul Lee

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  18. Diverse occupant behaviour and urban building heterogeneity to enhance urban building energy modelling

    Energy and Buildings · 2025-11-14

    Santhan Reddy Penaka, Kailun Feng, Thomas Olofsson, Weizhuo Lu

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  19. Predicting ride comfort in high-speed rail using machine learning

    High-speed Railway · 2026-05-01

    Amandeep Singh, Mani Entezami, Philippe Doyon-Poulin, Stephan Milosavljevic, Krishna Narayan Dewangan, Yash Kumar Dhabi, Siby Samuel, Graeme Yeo

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