يعرض 61 - 80 نتائج من 145 نتيجة بحث عن '(( binary base models optimization algorithm ) OR ( binary image models optimization algorithm ))*', وقت الاستعلام: 0.67s تنقيح النتائج
  1. 61

    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. …"
  2. 62

    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. …"
  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

    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. …"
  5. 65

    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. …"
  6. 66

    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. …"
  7. 67

    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. …"
  8. 68

    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. …"
  9. 69

    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. …"
  10. 70

    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. …"
  11. 71

    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. …"
  12. 72

    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. …"
  13. 73

    <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. …"
  14. 74

    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. …"
  15. 75

    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. …"
  16. 76

    DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx حسب Yuhong Huang (115702)

    منشور في 2021
    "…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"
  17. 77

    SHAP bar plot. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  18. 78

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

    منشور في 2025
    الموضوعات:
  19. 79

    Sample screening flowchart. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  20. 80

    Descriptive statistics for variables. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات: