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    Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms by Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim

    Published 2025-07-01
    “…The prediction of software defects is a crucial element in maintaining the stability and reliability of software systems. This research addresses this need by combining advanced techniques (ensemble techniques) with seventeen machine learning algorithms for predicting software defects, categorised into three types: semi-supervised, self-supervised, and supervised. …”
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  4. 64

    Improving Attack Detection in IoV with Class Balancing and Feature Selection by Thierry Widyatama, Ifan Rizqa, Fauzi Adi Rafrastara

    Published 2025-03-01
    “…The ensemble algorithms evaluated in this research comprise Random Forest, Gradient Boosting, and XGBoost. …”
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  5. 65

    Prediction of Anemia from Multi-Data Attribute Co-Existence by Talal Qadah, Asmaa Munshi

    Published 2024-01-01
    “…Therefore, this study has reevaluated the claims within the domain of detecting and predicting anemia with the best machine learning algorithm. Another research problem, lies with the fact that previous studies on anemia prediction utilized limited machine learning algorithms across a narrow range of datasets, whereas this current study employed numerous machine learning algorithms across a wide range of anemia datasets and tested three hypotheses. …”
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    Progress on the world’s primate hotspots and coldspots: modeling ensemble super SDMs in cloud-computers based on digital citizen-science big data and 200+ predictors for more susta... by Moriz Steiner, Falk Huettmann

    Published 2025-05-01
    “…These Super SDMs are conducted using an ensemble of modern Machine Learning algorithms, including Maxent, TreeNet, RandomForest, CART, CART Boosting and Bagging, and MARS with the utilization of cloud supercomputers (as an add-on option for more powerful models). …”
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    Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

    Published 2025-04-01
    “…The model features are selected with the Boruta wrapper algorithm based on the SAOCOM-1A images after pre-processing, and the SSRDC values at sampling locations within the research area are calculated with the reflected wave method based on the GPR data. …”
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    Cerebrospinal Fluid Leakage Combined with Blood Biomarkers Predicts Poor Wound Healing After Posterior Lumbar Spinal Fusion: A Machine Learning Analysis by Pang Z, Ou Y, Liang J, Huang S, Chen J, Huang S, Wei Q, Liu Y, Qin H, Chen Y

    Published 2024-11-01
    “…In the test group, logistic regression analysis, support vector machine (SVM), random forest (RF), decision tree (DT), XGboost, Naïve Bayes (NB), k-Nearest Neighbor (KNN), and Multi-Layer Perceptron (MLP) were used to identify specific variables. …”
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