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Showing 101 - 120 results of 166 for search '(( main research random tree algorithm ) OR (( fast OR east) research random three algorithm ))', query time: 0.33s Refine Results
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    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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    Unveiling shadows: A data-driven insight on depression among Bangladeshi university students by Sanjib Kumar Sen, Md. Shifatul Ahsan Apurba, Anika Priodorshinee Mrittika, Md. Tawhid Anwar, A.B.M. Alim Al Islam, Jannatun Noor

    Published 2025-01-01
    “…After rigorous analysis, Random Forest emerged as the best-performing algorithm, exhibiting remarkable accuracy (87%), precision (78%), recall (95%), and f1-score (86%). …”
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    Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

    Published 2025-05-01
    “… This paper aimed to investigate human emotion recognition through the analysis of facial expressions, using both classical machine learning methods and advanced techniques based on deep neural networks. The research compares the performance of classical machine learning algorithms (such as K-Nearest Neighbors, Gaussian Naive Bayes, Support Vector Machines, Adaptive Boosting, Decision Tree, and Random Forest) with the modern deep learning methods (such as Convolutional Neural Networks, Deep Neural Networks, and Recursive Neural Networks) using standardized datasets. …”
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    An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

    Published 2025-08-01
    “…In addition, the study area's hydro-chemical facies were examined, and machine learning models’ hyperparameters such as Random Forest (RF), Borda Scoring Algorithm (BSA), Decision Tree (DT), Multilayer Perception (MLP), and Naïve Bayes (NB), were executed before, to training and testing the samples of surface water. …”
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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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