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Showing 1 - 20 results of 3,710 for search '(( present study algorithm ) OR ((( present data algorithm ) OR ( neural coding algorithm ))))', query time: 0.71s Refine Results
  1. 1
    ML algorithms used in this study.

    ML algorithms used in this study. by Toheeb Salahudeen (21368040)

    Published 2025
    “…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
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  2. 2
    Data set presentation.

    Data set presentation. by Wenguang Li (6528113)

    Published 2024
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  3. 3
    Algorithm for the proposed work.

    Algorithm for the proposed work. by Shuvo Biswas (21728782)

    Published 2025
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  4. 4
    Comparison of the results achieved by the algorithm with the best <i>F</i>2 score against the results presented in [9].

    Comparison of the results achieved by the algorithm with the best <i>F</i>2 score against the results presented in [9]. by André G. Coimbra (21354135)

    Published 2025
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  5. 5
    An overview of the organization of the study program.

    An overview of the organization of the study program. by Marialuisa Gandolfi (8639238)

    Published 2024
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  6. 6
    Presents the overall disproportionality analysis results, demonstrating significant signal detection across all algorithms employed.

    Presents the overall disproportionality analysis results, demonstrating significant signal detection across all algorithms employed. by Shiyu Wang (813972)

    Published 2025
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  7. 7
    Parameters of LWQPSO-SOM algorithm.

    Parameters of LWQPSO-SOM algorithm. by Yiwei Zhao (2729758)

    Published 2025
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  8. 8
    Parameters of LWQPSO-SOM algorithm.

    Parameters of LWQPSO-SOM algorithm. by Yiwei Zhao (2729758)

    Published 2025
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  9. 9
    Algorithm performance comparison.

    Algorithm performance comparison. by Haiyan Wang (25821)

    Published 2025
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  10. 10
    Confusion Matrix for Subspace algorithm (3000 Learning Cycles) providing insight into the performance evaluation of Subspace algorithm.

    Confusion Matrix for Subspace algorithm (3000 Learning Cycles) providing insight into the performance evaluation of Subspace algorithm. by Sadia Nazim (21440115)

    Published 2025
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  11. 11
    R file for the elementary computations presented in Section 3.

    R file for the elementary computations presented in Section 3. by Jürgen Kampf (21354027)

    Published 2025
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  12. 12
    The workflow of the present study.

    The workflow of the present study. by Kaiyi Zhou (2553352)

    Published 2024
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  13. 13
    Statistical details of data presented in Fig 16.

    Statistical details of data presented in Fig 16. by Piotr Popik (292215)

    Published 2024
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  14. 14
    Statistical details of data presented in Fig 17.

    Statistical details of data presented in Fig 17. by Piotr Popik (292215)

    Published 2024
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  15. 15
    Clustering results of LWQPSO-SOM algorithm.

    Clustering results of LWQPSO-SOM algorithm. by Yiwei Zhao (2729758)

    Published 2025
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  16. 16
    The ANFIS algorithm details.

    The ANFIS algorithm details. by Mohammadmahdi Taheri (21722285)

    Published 2025
    “…To overcome the challenges involved in the selection of a stock portfolio, this article presents a three-stage optimization model. In the first stage, the pharmaceutical industry data collected from the Tehran Stock Exchange (TSE) website is used to apply the robust ratio data envelopment analysis (RR-DEA) in GAMS software with respect to some specific financial indicators to determine efficient stocks in conditions of data uncertainty. …”
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  17. 17
    Structure and the optimization technique of the algorithms adopted in the study.

    Structure and the optimization technique of the algorithms adopted in the study. by M. A. Habib (16839161)

    Published 2025
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  18. 18
    R file for the (co)variances of the real data presented in Section 3.

    R file for the (co)variances of the real data presented in Section 3. by Jürgen Kampf (21354027)

    Published 2025
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  19. 19
    R file for the logistic regression of the real data presented in Section 3.

    R file for the logistic regression of the real data presented in Section 3. by Jürgen Kampf (21354027)

    Published 2025
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  20. 20
    R file for the mean values of the real data presented in Section 3.

    R file for the mean values of the real data presented in Section 3. by Jürgen Kampf (21354027)

    Published 2025
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