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Showing 21 - 40 results of 3,614 for search '(( model selection algorithm ) OR ( code encryption algorithm ))', query time: 0.40s Refine Results
  1. 21
    Image 8_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 8_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  2. 22
    Image 7_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 7_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  3. 23
    Image 3_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 3_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  4. 24
    Image 10_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 10_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  5. 25
    Image 4_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 4_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  6. 26
    Image 6_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 6_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  7. 27
    Image 5_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 5_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  8. 28
    Image 1_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 1_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  9. 29
    Image 9_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 9_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…<p>In contemporary breeding programs, typically genomic best linear unbiased prediction (gBLUP) models are employed to drive decisions on artificial selection. …”
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  10. 30
    Accuracy of SVM-RFE Algorithm for Feature Selection.

    Accuracy of SVM-RFE Algorithm for Feature Selection. by Tianhua Chen (6124367)

    Published 2025
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  11. 31
    The algorithm of the AWGE-ESPCA model.

    The algorithm of the AWGE-ESPCA model. by Rui Miao (1592461)

    Published 2025
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  12. 32
    IRBMO vs. feature selection algorithm boxplot.

    IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

    Published 2025
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  13. 33
    Schematic representation of selection of neighboring pixels in FAST algorithm.

    Schematic representation of selection of neighboring pixels in FAST algorithm. by Muhammad Adeel Akram (20477098)

    Published 2024
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  14. 34
    Evaluation of model aggregation algorithms.

    Evaluation of model aggregation algorithms. by JiaMing Wang (334865)

    Published 2024
    “…Additionally, the paper introduces the Gradient Similarity Model Aggregation (GSA) algorithm, which dynamically selects and weights updates from different models to reduce communication overhead. …”
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  15. 35
    Variable selection procedure using the Boruta algorithm.

    Variable selection procedure using the Boruta algorithm. by Qiudie Liu (22655907)

    Published 2025
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  16. 36
    Data generation algorithm.

    Data generation algorithm. by Aluwani Ramalata (21262977)

    Published 2025
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  17. 37
    Comparison of the EODA algorithm with existing algorithms in terms of recall.

    Comparison of the EODA algorithm with existing algorithms in terms of recall. by Sunil Kumar (102321)

    Published 2025
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  18. 38
    Comparison of the EODA algorithm with existing algorithms in terms of precision.

    Comparison of the EODA algorithm with existing algorithms in terms of precision. by Sunil Kumar (102321)

    Published 2025
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  19. 39
    Optimal patch size and stride selection algorithm with stability constraints.

    Optimal patch size and stride selection algorithm with stability constraints. by Chenglong Ge (2626258)

    Published 2025
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  20. 40
    Top features identified by the stepwise additive feature selection algorithm.

    Top features identified by the stepwise additive feature selection algorithm. by Kylie K. Hornaday (9713558)

    Published 2025
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