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Showing 1 - 20 results of 34 for search '(( binary basic process optimization algorithm ) OR ( binary _ random optimization algorithm ))', query time: 0.31s Refine Results
  1. 1
    Random forest with hyperparameter optimization.

    Random forest with hyperparameter optimization. by Balraj Preet Kaur (20370832)

    Published 2024
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  2. 2
    Best optimizer results for random forest.

    Best optimizer results for random forest. by Balraj Preet Kaur (20370832)

    Published 2024
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  3. 3
    Best optimizer results of Random Forest.

    Best optimizer results of Random Forest. by Balraj Preet Kaur (20370832)

    Published 2024
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  4. 4
    Results of Random Forest.

    Results of Random Forest. by Balraj Preet Kaur (20370832)

    Published 2024
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  5. 5
    Top-performing model configuration and performance by algorithm type.

    Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

    Published 2025
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  6. 6
    ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.

    ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

    Published 2025
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  7. 7
    The accuracy score change matrix following model development.

    The accuracy score change matrix following model development. by Uğur Ejder (22683228)

    Published 2025
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  8. 8
    The comparison of the accuracy score of the benchmark and the proposed models.

    The comparison of the accuracy score of the benchmark and the proposed models. by Uğur Ejder (22683228)

    Published 2025
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  9. 9
    The prediction accuracy of simple versus hybrid models.

    The prediction accuracy of simple versus hybrid models. by Uğur Ejder (22683228)

    Published 2025
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  10. 10
    Flow diagram of the proposed model.

    Flow diagram of the proposed model. by Uğur Ejder (22683228)

    Published 2025
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  11. 11
    The statistical description of the original data set of the patients (<i>n</i> = 162).

    The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

    Published 2025
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  12. 12
    Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).

    Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). by Uğur Ejder (22683228)

    Published 2025
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  13. 13
    The most effective active substances for subfertility treatment.

    The most effective active substances for subfertility treatment. by Uğur Ejder (22683228)

    Published 2025
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  14. 14
    Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction.

    Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

    Published 2025
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  15. 15
    The list of parameters of the modified data set for machine learning (<i>n</i> = 162).

    The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)

    Published 2025
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  16. 16
    Flow diagram of the conversion of drugs into active substances.

    Flow diagram of the conversion of drugs into active substances. by Uğur Ejder (22683228)

    Published 2025
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  17. 17
    Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.

    Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

    Published 2025
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  18. 18
    Hyperparameters of the LSTM Model.

    Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

    Published 2025
    “…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …”
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  19. 19
    The AD-PSO-Guided WOA LSTM framework.

    The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

    Published 2025
    “…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …”
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  20. 20
    Prediction results of individual models.

    Prediction results of individual models. by Ahmed M. Elshewey (21463867)

    Published 2025
    “…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …”
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