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Showing 1 - 20 results of 77 for search '(( gene based bayesian optimization algorithm ) OR ( binary data were optimization algorithm ))', query time: 0.50s Refine Results
  1. 1
    Optimal ALARM BN discovered by CausNet.

    Optimal ALARM BN discovered by CausNet. by Nand Sharma (21519845)

    Published 2025
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  2. 2
    Optimal ovarian cancer BNs learned by CausNet and CausNet-partial.

    Optimal ovarian cancer BNs learned by CausNet and CausNet-partial. by Nand Sharma (21519845)

    Published 2025
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  3. 3
    Average FDR with and .

    Average FDR with and . by Nand Sharma (21519845)

    Published 2025
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  4. 4
    FDR and Runtime for ALARM.

    FDR and Runtime for ALARM. by Nand Sharma (21519845)

    Published 2025
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  5. 5
    FDR ().

    FDR (). by Nand Sharma (21519845)

    Published 2025
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  6. 6
    FDR ().

    FDR (). by Nand Sharma (21519845)

    Published 2025
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  7. 7
    ALARM networks with different partial orderings.

    ALARM networks with different partial orderings. by Nand Sharma (21519845)

    Published 2025
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  8. 8
    Average Runtime in seconds.

    Average Runtime in seconds. by Nand Sharma (21519845)

    Published 2025
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  9. 9
    Average Hamming Distance with and .

    Average Hamming Distance with and . by Nand Sharma (21519845)

    Published 2025
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  10. 10
    Average FDR with and .

    Average FDR with and . by Nand Sharma (21519845)

    Published 2025
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  11. 11
    Subset lattice for partial orderings with on four nodes .

    Subset lattice for partial orderings with on four nodes . by Nand Sharma (21519845)

    Published 2025
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  12. 12
    Subset lattices with parent set constraints.

    Subset lattices with parent set constraints. by Nand Sharma (21519845)

    Published 2025
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  13. 13
    Average Hamming Distance with and .

    Average Hamming Distance with and . by Nand Sharma (21519845)

    Published 2025
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  14. 14
    Subset lattice for BNs with four nodes .

    Subset lattice for BNs with four nodes . by Nand Sharma (21519845)

    Published 2025
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  15. 15
    Subset lattices with parent set constraints and best sinks identified by CausNet-partial as an example.

    Subset lattices with parent set constraints and best sinks identified by CausNet-partial as an example. by Nand Sharma (21519845)

    Published 2025
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  16. 16
    DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF

    DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF by Deniz Seçilmiş (13028616)

    Published 2022
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  17. 17
    DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF

    DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF by Deniz Seçilmiş (13028616)

    Published 2022
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  18. 18
    Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data

    Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data by Changhun Kim (682542)

    Published 2022
    “…In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. …”
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  19. 19
    A* Path-Finding Algorithm to Determine Cell Connections

    A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

    Published 2025
    “…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. …”
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  20. 20
    Datasets and their properties.

    Datasets and their properties. by Olaide N. Oyelade (14047002)

    Published 2023
    “…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
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