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Showing 81 - 100 results of 4,266 for search '(( algorithm machine function ) OR ( algorithms using function ))', query time: 0.32s Refine Results
  1. 81
    Machine learning.

    Machine learning. by Rui Guo (134395)

    Published 2025
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  2. 82
    10-fold cross-validation evaluation of accuracy of animal tracking algorithms.

    10-fold cross-validation evaluation of accuracy of animal tracking algorithms. by Catalin Mitelut (5587493)

    Published 2025
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  3. 83
    Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations.

    Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations. by Miray Unlu Yazici (14792680)

    Published 2025
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  4. 84
    MWOA-BiLSTM machine fault detection process.

    MWOA-BiLSTM machine fault detection process. by Yi-Qiang Xia (20161326)

    Published 2024
    “…Moreover, the Wilcoxon rank sum test is used to verify the effectiveness of the proposed algorithm. …”
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  5. 85
    Predicting CO<sub>2</sub> Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms

    Predicting CO<sub>2</sub> Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

    Published 2025
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  6. 86
    Predicting CO<sub>2</sub> Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms

    Predicting CO<sub>2</sub> Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

    Published 2025
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  7. 87
    Table 5_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 5_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  8. 88
    Table 8_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 8_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  9. 89
    Table 7_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 7_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  10. 90
    Table 4_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 4_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  11. 91
    Table 6_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 6_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  12. 92
    Table 3_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 3_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  13. 93
    Table 2_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 2_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  14. 94
    Table 1_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls

    Table 1_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
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  15. 95
    Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training.

    Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training. by Abeer Aljohani (18497914)

    Published 2025
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  16. 96
    This section provides medical data tables used in the experiment.

    This section provides medical data tables used in the experiment. by Jingjing Ma (419752)

    Published 2025
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  17. 97
    The results of gene ontology analysis of the hub genes, including (a) biological process, (b) cellular components, (c) molecular functions, and (d) pathway analysis.

    The results of gene ontology analysis of the hub genes, including (a) biological process, (b) cellular components, (c) molecular functions, and (d) pathway analysis. by Devi Soorya Narayana Sasikumar (22331743)

    Published 2025
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  18. 98
    Logistic kernel: Power and Type I error for cluster evaluation metric simulations.

    Logistic kernel: Power and Type I error for cluster evaluation metric simulations. by Alexandria M. Jensen (6494957)

    Published 2024
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  19. 99
    ABIDE dataset subject demographics.

    ABIDE dataset subject demographics. by Alexandria M. Jensen (6494957)

    Published 2024
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  20. 100
    Linear kernel: Power and Type I error for cluster evaluation metric simulations.

    Linear kernel: Power and Type I error for cluster evaluation metric simulations. by Alexandria M. Jensen (6494957)

    Published 2024
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