يعرض 21 - 40 نتائج من 50 نتيجة بحث عن '(( binary class data optimization algorithm ) OR ( binary class from optimization algorithm ))*', وقت الاستعلام: 0.47s تنقيح النتائج
  1. 21
  2. 22
  3. 23
  4. 24
  5. 25
  6. 26

    Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) حسب Daniel Pérez Palau (11097348)

    منشور في 2024
    "…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …"
  7. 27
  8. 28
  9. 29

    Summary of LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  10. 30

    SHAP analysis for LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  11. 31

    Comparison of intrusion detection systems. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  12. 32

    Parameter setting for CBOA and PSO. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  13. 33

    NSL-KDD dataset description. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  14. 34

    The architecture of LSTM cell. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  15. 35

    The architecture of ILSTM. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  16. 36

    Parameter setting for LSTM. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  17. 37

    Transformation of symbolic features in NSL-KDD. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  18. 38

    Programs to evaluate superoptimizer STOKE. حسب Przemysław Kowalewski (12893507)

    منشور في 2022
    "…The searching algorithm of STOKE is not always able to find programs that are at least as efficient as programs optimized by gcc -O3. …"
  19. 39

    Silibinin solubilization: combined effect of co-solvency and inclusion complex formation حسب Azam Dehghan (18434551)

    منشور في 2024
    "…<p>Belonging to the class II drugs according to the biopharmaceutics classification system, silibinin (SLB) benefits from high permeability but suffers poor solubility that negatively affects the development of any delivery system. …"
  20. 40

    Image processing workflow. حسب Denis Tamiev (7404980)

    منشور في 2020
    "…These annotated training images were passed to the cCNN to determine optimal network weights (e). The output of the network (from image depicted in panel c) is a confidence value for each sub-class (A–artifact; I—X–single through ten cell cluster), here presented in a radar chart (F). …"