Showing 61 - 80 results of 15,676 for search '(( algorithm a function ) OR ((( algorithm python function ) OR ( algorithm f1 function ))))*', query time: 1.35s Refine Results
  1. 61

    Multimodal reference functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  2. 62

    Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

    Published 2019
    “…These implementations need to utilize high-precision arithmetic, and are programmed in the Python programming language. A thorough comparison with existing R functions allows the identification of cases when the latter fail, and provide further guidance to their use.…”
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    The convergence curves of the test functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  11. 71

    Single-peaked reference functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  12. 72

    Comparison of algorithms in two cases. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
  13. 73

    Flow of the NSGA-II algorithm. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
  14. 74

    Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  15. 75

    Fixed-dimensional multimodal reference functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  16. 76

    Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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