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Showing 1 - 6 results of 6 for search '(( binary deep learning motivation algorithm ) OR ( binary amp bayesian optimization algorithm ))', query time: 0.44s Refine Results
  1. 1
    Performance metrics of the machine learning models on the test dataset.

    Performance metrics of the machine learning models on the test dataset. by Kengo Oka (1420585)

    Published 2025
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  2. 2
    Association between deep bite and oral habits.

    Association between deep bite and oral habits. by Kengo Oka (1420585)

    Published 2025
    “…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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  3. 3
    Association between crowding and oral habits.

    Association between crowding and oral habits. by Kengo Oka (1420585)

    Published 2025
    “…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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  4. 4
    Breakdown of participants by residential area.

    Breakdown of participants by residential area. by Kengo Oka (1420585)

    Published 2025
    “…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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  5. 5
    Each variable for the dataset.

    Each variable for the dataset. by Kengo Oka (1420585)

    Published 2025
    “…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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  6. 6
    Deep Discrete Encoders: Identifiable Deep Generative Models for Rich Data with Discrete Latent Layers

    Deep Discrete Encoders: Identifiable Deep Generative Models for Rich Data with Discrete Latent Layers by Seunghyun Lee (1372719)

    Published 2025
    “…Extensive simulation studies for high-dimensional data and deep architectures validate our theoretical results and demonstrate the excellent performance of our algorithms. …”
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