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feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
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Showing 1 - 20 results of 184 for search '(( primary data feature optimization algorithm ) OR ( binary wave driven optimization algorithm ))', query time: 0.60s Refine Results
  1. 1
    Features selected by optimization algorithms.

    Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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  2. 2
    Average number of selected features.

    Average number of selected features. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  3. 3
    Average number of selected features.

    Average number of selected features. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  4. 4
    Hybrid feature selection algorithm of CSCO-ROA.

    Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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  5. 5
    S1 Data -

    S1 Data - by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  6. 6
    Parameter settings for algorithms.

    Parameter settings for algorithms. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  7. 7
    Parameter settings for algorithms.

    Parameter settings for algorithms. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  8. 8
    Variable importance of features included in the gradient boosting machine learning (XGB) algorithm for predicting postinduction hypotension.

    Variable importance of features included in the gradient boosting machine learning (XGB) algorithm for predicting postinduction hypotension. by Manabu Yoshimura (11040049)

    Published 2022
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  9. 9
    Average runtime of different algorithms.

    Average runtime of different algorithms. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  10. 10
    Average runtime of different algorithms.

    Average runtime of different algorithms. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  11. 11
    Flowchart of GJO-GWO algorithm.

    Flowchart of GJO-GWO algorithm. by Guangwei Liu (181992)

    Published 2024
    “…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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  12. 12
    Input features.

    Input features. by Nicola Lazzarini (3528197)

    Published 2022
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  13. 13
    Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF

    Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by Josefa Díaz-Álvarez (5572427)

    Published 2022
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  14. 14
    Data_Sheet_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF

    Data_Sheet_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by Josefa Díaz-Álvarez (5572427)

    Published 2022
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  15. 15
    Age feature importance.

    Age feature importance. by Nicola Lazzarini (3528197)

    Published 2022
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  16. 16
    Schematic representation of univariate ensemble-based feature selection.

    Schematic representation of univariate ensemble-based feature selection. by Nanavath Kiran Singh Nayak (22184565)

    Published 2025
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  17. 17
    Most important predictive features.

    Most important predictive features. by Nicola Lazzarini (3528197)

    Published 2022
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  18. 18
    Optimized model prediction performance.

    Optimized model prediction performance. by Guang Tu (22054865)

    Published 2025
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  19. 19
    Data_Sheet_1_How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework.ZIP

    Data_Sheet_1_How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework.ZIP by Hao Wu (65943)

    Published 2022
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  20. 20
    MLP vs classification algorithms.

    MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

    Published 2024
    “…However, SDP faces challenges like imbalanced data, high-dimensional features, model overfitting, and outliers. …”
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