Showing 101 - 120 results of 146 for search '(( primary data process optimization algorithm ) OR ( binary data driven optimization algorithm ))*', query time: 0.70s Refine Results
  1. 101

    Analysis PC2 AU-ROC curve. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  2. 102

    PROMISE defects prediction attribute aspects. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  3. 103

    Internal architecture of the SPAM-XAI model. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  4. 104

    SPAM-XAI compared with previous models. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  5. 105

    SPAM-XAI confusion matrix using PC2 dataset. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  6. 106

    Overview of SPAM-XAI model complete architecture. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  7. 107

    SPAM-XAI using the PC1 dataset. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  8. 108

    SPAM-XAI using the CM1 dataset. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  9. 109

    Analysis of CM1 ROC curve. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  10. 110

    SPAM-XAI confusion matrix using PC1 dataset. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  11. 111

    Analysis PC1 AU-ROC curve. by Mohd Mustaqeem (19106494)

    Published 2024
    “…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
  12. 112

    Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

    Published 2025
    “…RSEE projects heterogeneous input data into an exertion-conditioned latent space, aligning model predictions with observed physiological variance and mitigating false positives by explicitly modeling the overlap between athletic remodeling and subclinical pathology.…”
  13. 113

    Proposed method approach. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  14. 114

    LSTM model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  15. 115

    Descriptive statistics. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  16. 116

    CNN-LSTM Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  17. 117

    MLP Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  18. 118

    RNN Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  19. 119

    CNN Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
  20. 120

    Bi-directional LSTM Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”