يعرض 41 - 60 نتائج من 87 نتيجة بحث عن 'binary based model optimization algorithm', وقت الاستعلام: 0.19s تنقيح النتائج
  1. 41

    Results of Decision tree. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  2. 42

    Adaboost classifier results. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  3. 43

    Results of Lightbgm. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  4. 44

    Results of Lightbgm. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  5. 45

    Feature selection process. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  6. 46

    Results of KNN. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  7. 47

    After upsampling. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  8. 48

    Results of Extra tree. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  9. 49

    Gradient boosting classifier results. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  10. 50

    The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  11. 51

    IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  12. 52

    IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  13. 53

    SHAP bar plot. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  14. 54

    Display of the web prediction interface. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  15. 55

    Sample screening flowchart. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  16. 56

    Descriptive statistics for variables. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  17. 57

    SHAP summary plot. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  18. 58

    Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

    منشور في 2024
    "…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"
  19. 59

    A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

    منشور في 2025
    "…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…"
  20. 60

    Plan frame of the house. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"