يعرض 61 - 80 نتائج من 150 نتيجة بحث عن '(( binary base model optimization algorithm ) OR ( binary task based optimization algorithm ))*', وقت الاستعلام: 0.48s تنقيح النتائج
  1. 61

    Dataset description. 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. 62

    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. …"
  3. 63

    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. …"
  4. 64

    Results of Adaboost. 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. 65

    Results of Random Forest. 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. 66

    Before 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. …"
  7. 67

    Results of gradient boosting classifier. 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. 68

    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. …"
  9. 69

    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. …"
  10. 70

    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. …"
  11. 71

    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. …"
  12. 72

    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. …"
  13. 73

    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. …"
  14. 74

    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. …"
  15. 75

    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. …"
  16. 76

    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. …"
  17. 77
  18. 78

    ROC curves for the test set of four models. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  19. 79
  20. 80

    <i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

    منشور في 2023
    "…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i><sub><i>δ</i></sub>, <i>hi</i>PRS constructs <i>I</i><sub><i>K</i></sub>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …"