Showing 1 - 20 results of 834 for search 'Random binary three', query time: 0.16s Refine Results
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    Random Generalized Additive Logistic Forest: A Novel Ensemble Method for Robust Binary Classification by Oyebayo Ridwan Olaniran, Ali Rashash R. Alzahrani, Nada MohammedSaeed Alharbi, Asma Ahmad Alzahrani

    Published 2025-04-01
    “…We introduce a novel ensemble approach, the Random Generalized Additive Logistic Forest (RGALF), which integrates generalized additive models (GAMs) within a random forest framework to improve binary classification tasks. …”
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    Evaluating the three-level approach of the U-smile method for imbalanced binary classification. by Barbara Więckowska, Katarzyna B Kubiak, Przemysław Guzik

    Published 2025-01-01
    “…Real-life binary classification problems often involve imbalanced datasets, where the majority class outnumbers the minority class. …”
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    CREDIT CARD FRAUD DETECTION USING LINEAR DISCRIMINANT ANALYSIS (LDA), RANDOM FOREST, AND BINARY LOGISTIC REGRESSION by Muhammad Ahsan, Tabita Yuni Susanto, Tiza Ayu Virania, Andi Indra Jaya

    Published 2022-12-01
    “…In this research, we describe fraud detection as a classification issue by comparing three methods. The method used is Linear Discriminant Analysis (LDA), Random Forest, and Binary Logistic Regression. …”
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    SBS Suppression Capability of Optimized Pseudo-Random Binary Sequence Phase Modulation in Multi-Stage Fiber Amplifiers by He Wang, Yifeng Yang, Kaiyuan Wang, Qianhe Shao, Xinyu Duan, Xiaolong Chen, Kai Liu, Xiaoqiang Xiong, Junqing Meng, Bing He

    Published 2025-01-01
    “…We demonstrate the capability to suppress stimulated Brillouin scattering (SBS) in a high-power all-fiber laser amplifier system using filtered and amplified pseudo-random binary sequence (PRBS) phase modulation techniques. …”
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    A Multi-Kernel Mode Using a Local Binary Pattern and Random Patch Convolution for Hyperspectral Image Classification by Wei Huang, Yao Huang, Zebin Wu, Junru Yin, Qiqiang Chen

    Published 2021-01-01
    “…In order to improve classification performance while reducing costs, this article proposes a multikernel method based on a local binary pattern and random patches (LBPRP-MK), which integrates a local binary pattern (LBP) and deep learning into a multiple-kernel framework. …”
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    Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest by Lu Huang, Lu Huang, Xin Liu, Jiang Yi, Yu-Wei Jiao, Tian-Qi Zhang, Guang-Yao Zhu, Shu-Yue Yu, Zhong-Liang Liu, Min Gao, Xiao-Qin Duan

    Published 2025-04-01
    “…The subject was classified as either Success or Unsuccess group according to whether they had completed the on-road test. A random forest algorithm was then applied to construct a binary classification model based on the data obtained from the two groups.ResultsCompared to the Unsuccess group, the Success group had higher scores on the OCS scale for “crossing out the intact heart” (p = 0.015) and lower scores for “executive function” (p = 0.009). …”
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    Wide Binaries from GAIA DR3 : testing GR vs MOND with realistic triple modelling by Charalambos Pittordis, Will Sutherland, Paul Shepherd

    Published 2025-08-01
    “…We provide an updated test for modifications of gravity from a sample of wide-binary stars from Gaia DR3, and their sky-projected relative velocities. …”
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