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adoption classification » emotion classification (Expand Search), actions classification (Expand Search), modulation classification (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based adoption » based adaptation (Expand Search), based motion (Expand Search), based action (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
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Showing 1 - 5 results of 5 for search '(( binary based adoption classification algorithm ) OR ( binary 2 wolf optimization algorithm ))', query time: 0.95s Refine Results
  1. 1
    AUC score comparison table for all the deep learning algorithms.

    AUC score comparison table for all the deep learning algorithms. by Khandaker Mohammad Mohi Uddin (13124356)

    Published 2024
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  2. 2
    Comparative overview of all DL and ML algorithms parameters in used in this study.

    Comparative overview of all DL and ML algorithms parameters in used in this study. by Khandaker Mohammad Mohi Uddin (13124356)

    Published 2024
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  3. 3
    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment

    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

    Published 2019
    “…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”
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  4. 4
    Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective

    Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)

    Published 2021
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  5. 5
    30-Meter Resolution Dataset of Abandoned and Reclaimed Croplands in Inner Mongolia, China (2000-2022)

    30-Meter Resolution Dataset of Abandoned and Reclaimed Croplands in Inner Mongolia, China (2000-2022) by Deji Wuyun (18440981)

    Published 2024
    “…This method enables precise classification of cultivation status and adopts a binary classification strategy with adaptive optimization, improving the efficiency of sample generation for the Random Forest algorithm. …”
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