يعرض 321 - 340 نتائج من 3,028 نتيجة بحث عن 'based selective algorithm', وقت الاستعلام: 0.23s تنقيح النتائج
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    Research on Olympic medal prediction based on GA-BP and logistic regression model checklist حسب Sanglin Zhao (20599835)

    منشور في 2025
    "…By estimating the number of Olympic gold medals and total medals, verifying the accuracy of the model, and predicting the medal table for the 2028 Los Angeles Olympics. Meanwhile, based on the synthetic control model, Estonia and China were selected as research subjects to construct a virtual control group and two experimental groups for analysis.…"
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    Different algorithms’ performance across 8 cores. حسب Yongan Feng (7345193)

    منشور في 2024
    "…<div><p>To address the instability and performance issues of the classical K-Means algorithm when dealing with massive datasets, we propose SOSK-Means, an improved K-Means algorithm based on Spark optimization. …"
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    Different algorithms’ performance across 4 cores. حسب Yongan Feng (7345193)

    منشور في 2024
    "…<div><p>To address the instability and performance issues of the classical K-Means algorithm when dealing with massive datasets, we propose SOSK-Means, an improved K-Means algorithm based on Spark optimization. …"
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    F1-scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Under the framework of model averaging, this paper proposes a criterion for the selection of weights in the aggregation of multiple models, employing a focal loss function with Mallows’ form to assign weights to the base models. …"
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    Interpretable QSAR modelling for immunotoxicity prediction using enhanced fingerprint and SHAP-based feature selection حسب D.R. Shin (22565122)

    منشور في 2025
    "…Three tree-based machine learning algorithms, in conjunction with robust feature selection techniques, were employed to identify critical molecular determinants associated with immunosuppressive effects. …"
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    Flow diagram of the patient selection process. حسب Li Wang (15202)

    منشور في 2024
    "…Finally, a unique double-layer stacking model is designed to improve the performance of the algorithm. Seven classical artificial intelligence methods of Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (ADB), Extra Tree (ET), and Gradient Boosting Decision Tree (GBDT) were selected as candidate models for the base model of the first layer of the model, and extreme gradient enhancement (XGBOOST) was selected as the meta-model for the second layer.…"
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