يعرض 1 - 20 نتائج من 705 نتيجة بحث عن 'multiple data ((conventional algorithm) OR (selection algorithm))', وقت الاستعلام: 0.25s تنقيح النتائج
  1. 1

    Algorithm for MFISTA-VA [30]. حسب Faisal Najeeb (20542714)

    منشور في 2025
    "…GRASP uses Temporal Total Variation (TV) norm as a sparsity transform to promote sparsity among multi-coil MRI data and Nonlinear Conjugate Gradient (NL-CG) algorithm to obtain an optimal solution. …"
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    AUC scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"
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    Recall scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"
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    F1-scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"
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    IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To address this problem, this paper proposes an improved red-billed blue magpie algorithm (IRBMO), which is specifically optimized for the feature selection task, and significantly improves the performance and efficiency of the algorithm on medical data by introducing multiple innovative behavioral strategies. …"
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    The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To address this problem, this paper proposes an improved red-billed blue magpie algorithm (IRBMO), which is specifically optimized for the feature selection task, and significantly improves the performance and efficiency of the algorithm on medical data by introducing multiple innovative behavioral strategies. …"
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    HMM to infer selection. حسب Adam G. Fine (21763286)

    منشور في 2025
    الموضوعات:
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    IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To address this problem, this paper proposes an improved red-billed blue magpie algorithm (IRBMO), which is specifically optimized for the feature selection task, and significantly improves the performance and efficiency of the algorithm on medical data by introducing multiple innovative behavioral strategies. …"
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    Feature selection using Boruta algorithm. حسب Shayla Naznin (13014015)

    منشور في 2025
    "…</p><p>Methods</p><p>Multiple machine learning (ML) algorithms were applied to data from the 2022 Bangladesh Demographic Health Survey, including Random Forest, Decision Tree, K-Nearest Neighbors, Logistic Regression, Support Vector Machine, XGBoost, LightGBM and Neural Networks. …"
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    Multi spatiotemporal perspective adjustment. حسب Qun Zhao (603175)

    منشور في 2025
    "…Firstly, we utilize existing geographic and topographic indicators to identify and select watersheds that exhibit similarities. Subsequently, we establish an initial regression model using the TrAdaBoost algorithm based on the hydrologic data from the selected watershed stations. …"
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    Initial model prediction results. حسب Qun Zhao (603175)

    منشور في 2025
    "…Firstly, we utilize existing geographic and topographic indicators to identify and select watersheds that exhibit similarities. Subsequently, we establish an initial regression model using the TrAdaBoost algorithm based on the hydrologic data from the selected watershed stations. …"
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    Station topographic index. حسب Qun Zhao (603175)

    منشور في 2025
    "…Firstly, we utilize existing geographic and topographic indicators to identify and select watersheds that exhibit similarities. Subsequently, we establish an initial regression model using the TrAdaBoost algorithm based on the hydrologic data from the selected watershed stations. …"