يعرض 1 - 20 نتائج من 9,936 نتيجة بحث عن '(( data using algorithm ) OR ((( develop tree algorithm ) OR ( element data algorithm ))))', وقت الاستعلام: 0.47s تنقيح النتائج
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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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    Comparison of different optimization algorithms. حسب Hang Zhao (143592)

    منشور في 2025
    الموضوعات: "…crayfish optimization algorithm…"
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    Algorithmic experimental parameter design. حسب Chuanxi Xing (20141665)

    منشور في 2024
    "…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …"
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    Spatial spectrum estimation for three algorithms. حسب Chuanxi Xing (20141665)

    منشور في 2024
    "…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …"
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    The run time for each algorithm in seconds. حسب Edward Antonian (21453161)

    منشور في 2025
    "…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …"
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    Variables tested in the ML algorithms. حسب Gilson Yuuji Shimizu (19837946)

    منشور في 2024
    "…Data from Beth Israel Deaconess Medical Center (BIDMC), USA, were used for external validation. …"
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    bppMigration-algorithms-data.tgz حسب Ziheng Yang (22169779)

    منشور في 2025
    "…<p dir="ltr">Population phylogenomics uses sampled genomes to jointly infer population genetic processes (ancestral and contemporary population sizes, historical gene flow) and a phylogenetic tree relating species or populations including species divergence times. …"
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    Risk element category diagram. حسب Yao Hu (3479972)

    منشور في 2025
    "…This article extracted features related to risk assessment, such as weather factors, airport facility inspections, and security check results, and conducted qualitative and quantitative analysis on these features to generate a datable risk warning weight table. This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …"
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    Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

    منشور في 2025
    "…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"
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    Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

    منشور في 2025
    "…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"
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    Data Sheet 4_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

    منشور في 2025
    "…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"
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    Data Sheet 6_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.docx حسب Cong Peng (160287)

    منشور في 2025
    "…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"
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    Data Sheet 1_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.pdf حسب Cong Peng (160287)

    منشور في 2025
    "…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"