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Showing 1 - 20 results of 53 for search '(( game ((teer decrease) OR (mean decrease)) ) OR ( ai ((larger decrease) OR (marked decrease)) ))', query time: 0.52s Refine Results
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    K-means results. by Fei Zhang (85787)

    Published 2025
    “…By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”
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    Feature importance result of SHAP. by Fei Zhang (85787)

    Published 2025
    “…By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”
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    Definition of variables. by Fei Zhang (85787)

    Published 2025
    “…By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”
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    Result of random forest. by Fei Zhang (85787)

    Published 2025
    “…By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”
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    Tree cover limits occupancy of a declining game bird by Bradley Kubecka (7387181)

    Published 2025
    “…Probability of bobwhite occupancy decreased as canopy cover increased (β<em><sub>Tree</sub></em> = -0.74, 95% CrI: -1.29 – -0.28); occupancy was over 19 times higher when canopy cover was 44% versus the mean observed value of 80.8% (range: 38–96%). …”
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    A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

    Published 2025
    “…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”