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Showing 1 - 20 results of 2,123 for search '(((( complement ii algorithm ) OR ( element data algorithm ))) OR ( level learning algorithm ))', query time: 0.40s Refine Results
  1. 1
    Example measurement and analysis units for landscape elements.

    Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

    Published 2025
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  2. 2
    Folder with all data and algorithms

    Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

    Published 2025
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  3. 3
    Description of the dataset used for the machine learning algorithm.

    Description of the dataset used for the machine learning algorithm. by Tri Ngo Quang (20390189)

    Published 2024
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  4. 4
    Phenotype frequencies for each mutant and for complementation testing.

    Phenotype frequencies for each mutant and for complementation testing. by McKenna Feltes (11242085)

    Published 2025
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  5. 5
    The accuracy of all employed learning algorithms.

    The accuracy of all employed learning algorithms. by Quan Shao (20148209)

    Published 2024
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  6. 6
    Performance of different machine learning algorithms.

    Performance of different machine learning algorithms. by Apichat Suratanee (634281)

    Published 2024
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  7. 7
    Framework of the machine learning algorithm for single-family housing price.

    Framework of the machine learning algorithm for single-family housing price. by Jaewon Han (8660295)

    Published 2025
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  8. 8
    Learning curves under various machine algorithms.

    Learning curves under various machine algorithms. by Jinlin Teng (17972595)

    Published 2024
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  9. 9
    Phenotype frequency and complementation for additional novel DY alleles.

    Phenotype frequency and complementation for additional novel DY alleles. by McKenna Feltes (11242085)

    Published 2025
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  10. 10
    Elements: Kingfisher: Storage Management for Data Federations (CSSI PI Meeting 2025)

    Elements: Kingfisher: Storage Management for Data Federations (CSSI PI Meeting 2025) by Brian Bockelman (5128082)

    Published 2025
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  11. 11
    Comparison results between the state-of-the-art algorithms and the proposed deep learning models for liquid level detection in terms of Accuracy.

    Comparison results between the state-of-the-art algorithms and the proposed deep learning models for liquid level detection in terms of Accuracy. by Dong Wang (73290)

    Published 2025
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  12. 12
    Trainable parameters for different algorithms.

    Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

    Published 2024
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  13. 13
    Machine Learning Models for Efficient Property Prediction of ABX<sub>3</sub> Materials: A High-Throughput Approach

    Machine Learning Models for Efficient Property Prediction of ABX<sub>3</sub> Materials: A High-Throughput Approach by Soundous Touati (20282599)

    Published 2024
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  14. 14
    Machine Learning Models for Efficient Property Prediction of ABX<sub>3</sub> Materials: A High-Throughput Approach

    Machine Learning Models for Efficient Property Prediction of ABX<sub>3</sub> Materials: A High-Throughput Approach by Soundous Touati (20282599)

    Published 2024
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  15. 15
    Machine Learning Models for Efficient Property Prediction of ABX<sub>3</sub> Materials: A High-Throughput Approach

    Machine Learning Models for Efficient Property Prediction of ABX<sub>3</sub> Materials: A High-Throughput Approach by Soundous Touati (20282599)

    Published 2024
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  16. 16
    Flowchart of the RIR algorithm.

    Flowchart of the RIR algorithm. by Jiamin Hu (8972420)

    Published 2024
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  17. 17
    Risk element category diagram.

    Risk element category diagram. by Yao Hu (3479972)

    Published 2025
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  18. 18
    Feature importance comparison between the machine learning algorithms used in this study.

    Feature importance comparison between the machine learning algorithms used in this study. by Sukanta Chakraborty (22693681)

    Published 2025
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  19. 19
    Supplementary data for "Algorithm-level data-guided correction for class imbalance in biological machine learning predictions: Protein interactions as a case"

    Supplementary data for "Algorithm-level data-guided correction for class imbalance in biological machine learning predictions: Protein interactions as a case" by Ebrahim Barzegari (21152114)

    Published 2025
    “…Correct and efficient use of algorithm-level methods, on the other hand, needs paying heed to data structure and content. …”
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  20. 20
    Significance levels of gene biomarkers.

    Significance levels of gene biomarkers. by Zongjin Li (38031)

    Published 2025
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