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Showing 41 - 60 results of 13,040 for search '(( algorithm python function ) OR ( ((algorithm pca) OR (algorithm used)) function ))', query time: 0.27s Refine Results
  1. 41
    S1 File -

    S1 File - by Yuh-Chin T. Huang (17867207)

    Published 2024
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  2. 42
    S1 Dataset -

    S1 Dataset - by Yuh-Chin T. Huang (17867207)

    Published 2024
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  3. 43
    PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call.

    PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

    Published 2025
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  4. 44
    Pseudo algorithm of the GA algorithm used in this study.

    Pseudo algorithm of the GA algorithm used in this study. by Tuan Anh Pham (1346049)

    Published 2020
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  5. 45
    Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection

    Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

    Published 2025
    “…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. …”
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  6. 46
    Curves of sigmoid functions used in our proposed algorithm.

    Curves of sigmoid functions used in our proposed algorithm. by Binh Thanh Dang (12368831)

    Published 2022
    “…<p>Curves of sigmoid functions used in our proposed algorithm.</p>…”
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  7. 47
    Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic

    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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  8. 48
    Principal Component Analysis (PCA) of the independent dataset from the HPC cohort.

    Principal Component Analysis (PCA) of the independent dataset from the HPC cohort. by Erica A. K. DePasquale (11851483)

    Published 2021
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  9. 49
    The used test functions in the evaluation.

    The used test functions in the evaluation. by Xuan Chen (158617)

    Published 2021
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  10. 50
    MSEs for the adaptive filtering algorithms by using hyperbolic functions.

    MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

    Published 2021
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  11. 51
    MSEs for the adaptive filtering algorithms by using hyperbolic functions.

    MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

    Published 2021
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  12. 52
    MSEs for the adaptive filtering algorithms by using hyperbolic functions.

    MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

    Published 2021
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  13. 53
    MSEs for the adaptive filtering algorithms by using hyperbolic functions.

    MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

    Published 2021
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  14. 54
    Flowchart for the genetic algorithm used in this article.

    Flowchart for the genetic algorithm used in this article. by Behnam Kia (6111551)

    Published 2020
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  15. 55
    Algorithmic flow of the verifiable delay function.

    Algorithmic flow of the verifiable delay function. by Xinhao Zheng (16637664)

    Published 2024
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  16. 56
    Comparison of algorithms in two cases.

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

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  17. 57
    Flow of the NSGA-II algorithm.

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

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  18. 58
    ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space

    ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

    Published 2020
    “…The “ADT” program can be efficiently used to (a) formulate analytic functional forms of differential equations for ADT angles and diabatic potential energy matrix and (b) solve the set of coupled differential equations numerically to evaluate ADT angles, residue due to singularity­(ies), ADT matrices, and finally, diabatic potential energy surfaces (PESs). …”
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  19. 59
    Schematics for gmxapi operations.

    Schematics for gmxapi operations. by M. Eric Irrgang (4487278)

    Published 2022
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  20. 60
    gmxapi usage examples.

    gmxapi usage examples. by M. Eric Irrgang (4487278)

    Published 2022
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