Showing 21 - 36 results of 36 for search '(( binary like features optimization algorithm ) OR ( binary risk based optimization algorithm ))', query time: 0.50s Refine Results
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    SHAP summary plot. by Meng Cao (105914)

    Published 2025
    Subjects:
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    Classification baseline performance. by Doaa Sami Khafaga (21463870)

    Published 2025
    “…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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    ANOVA test result. by Doaa Sami Khafaga (21463870)

    Published 2025
    “…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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    Summary of literature review. by Doaa Sami Khafaga (21463870)

    Published 2025
    “…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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    Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data by Fei Xue (24567)

    Published 2021
    “…In this article, we develop a novel angle-based approach to search the optimal DTR under a multicategory treatment framework for survival data. …”
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    Supplementary Material 8 by Nishitha R Kumar (19750617)

    Published 2025
    “…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”
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    Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

    Published 2025
    “…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …”
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    Models and Dataset by M RN (9866504)

    Published 2025
    “…The algorithm does not rely on predefined control parameters like crossover or mutation rates, which makes it lightweight and easy to implement for various feature selection and optimization tasks.…”