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models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
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Showing 1 - 20 results of 54 for search '(( dietary data models optimization algorithm ) OR ( binary sample design optimization algorithm ))', query time: 0.53s Refine Results
  1. 1
    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale.

    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

    Published 2023
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  2. 2
    Default and optimized parameters for each predictive model.

    Default and optimized parameters for each predictive model. by Emily S. Nichols (8740029)

    Published 2022
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  3. 3
    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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  4. 4
    Personal algorithmic recommendations of potassium and phosphorous intake and the corresponding concentration predictions.

    Personal algorithmic recommendations of potassium and phosphorous intake and the corresponding concentration predictions. by Jari Turkia (17912475)

    Published 2024
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  5. 5
    Nutrient predictors of the model.

    Nutrient predictors of the model. by Jari Turkia (17912475)

    Published 2024
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  6. 6
    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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  7. 7
    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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  8. 8
    Flow diagram of the proposed model.

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

    Published 2025
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  9. 9
    Comparison of model structures for personal nutrient effects.

    Comparison of model structures for personal nutrient effects. by Jari Turkia (17912475)

    Published 2024
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  10. 10
    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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  11. 11
    Correlation plot of matrix C<sub><i>b</i></sub> that includes the estimated within-model and cross-model correlations of personal effects.

    Correlation plot of matrix C<sub><i>b</i></sub> that includes the estimated within-model and cross-model correlations of personal effects. by Jari Turkia (17912475)

    Published 2024
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  12. 12
    DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF

    DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF by Eva Gonzalez-Flo (5046737)

    Published 2023
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  13. 13
    Correlation plot of matrix C<sub><i>g</i></sub> that includes the estimated within-model and cross-model correlations in level of dialysis treatment.

    Correlation plot of matrix C<sub><i>g</i></sub> that includes the estimated within-model and cross-model correlations in level of dialysis treatment. by Jari Turkia (17912475)

    Published 2024
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  14. 14
    Posterior predictive check (PPC) of the final nutritional effect model.

    Posterior predictive check (PPC) of the final nutritional effect model. by Jari Turkia (17912475)

    Published 2024
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  15. 15
    Structure of the graphical model with general, treatment, and personal level nutrient effects.

    Structure of the graphical model with general, treatment, and personal level nutrient effects. by Jari Turkia (17912475)

    Published 2024
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  16. 16
    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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  17. 17
    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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  18. 18
    Data collection during the patients’ usual treatment routine.

    Data collection during the patients’ usual treatment routine. by Jari Turkia (17912475)

    Published 2024
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  19. 19
    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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  20. 20
    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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