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Showing 61 - 80 results of 634 for search '(((( complement lasso algorithm ) OR ( elements based algorithm ))) OR ( level coding algorithm ))', query time: 0.44s Refine Results
  1. 61
    Expression levels of mRNA in the spinal cord of each group of rats.

    Expression levels of mRNA in the spinal cord of each group of rats. by Yufeng He (5673119)

    Published 2025
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  2. 62
    Code and raw data used in this study.

    Code and raw data used in this study. by Zhuolin Yang (14658411)

    Published 2024
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  3. 63
    The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset.

    The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

    Published 2025
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  4. 64
    Observed and predicted frequency of each algorithm combination of community-acquired pneumonia (CAP) in Model-3 in the primary analysis.

    Observed and predicted frequency of each algorithm combination of community-acquired pneumonia (CAP) in Model-3 in the primary analysis. by Jia Wei (120974)

    Published 2025
    “…<p>The columns indicate specific combinations, with filled circles denote an algorithm being positive in each combination. Codes: CAP primary diagnostic codes; Indication: CAP antibiotic indication; Radiology: chest X-ray report or CT scan report; Tests: shortness of breath and elevated C-reactive protein levels.…”
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  5. 65
    Model-Based Clustering of Categorical Data Based on the Hamming Distance

    Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

    Published 2024
    “…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …”
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  6. 66
    Image processing algorithm.

    Image processing algorithm. by Madison Shoraka (22171205)

    Published 2025
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  7. 67
    Computation time as a function of the sample size on the chain graph dataset.

    Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  8. 68
    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  9. 69
    Computation time as a function of the sample size on the random graph dataset.

    Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  10. 70
    F1 score of edges selected through cross-validation on the chain graph dataset.

    F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  11. 71
    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  12. 72
    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10).

    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10). by Tomokaze Shiratori (9635271)

    Published 2024
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  13. 73
    Number of edges selected through cross-validation on the chain graph dataset.

    Number of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  14. 74
    Number of edges selected through cross-validation on the random graph dataset.

    Number of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  15. 75
    Graphs of the regularization terms.

    Graphs of the regularization terms. by Tomokaze Shiratori (9635271)

    Published 2024
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  16. 76
    F1 score of a given number of selected edges on the chain graph dataset.

    F1 score of a given number of selected edges on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  17. 77
    Computation time as a function of the number of variables on the chain graph dataset.

    Computation time as a function of the number of variables on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  18. 78
    Computation time as a function of the number of variables on the random graph dataset.

    Computation time as a function of the number of variables on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  19. 79
    F1 score of a given number of selected edges on the random graph dataset.

    F1 score of a given number of selected edges on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  20. 80
    F1 score of edges selected through cross-validation on the random graph dataset.

    F1 score of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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