Showing 61 - 80 results of 77,582 for search '(( significant models based ) OR ( significant ((point decrease) OR (nn decrease)) ))', query time: 1.16s Refine Results
  1. 61

    PLS-SEM bootstrapping model significant estimation. by Ghulam Raza Sargani (9455118)

    Published 2021
    Subjects: “…entrepreneurial activities based…”
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    MAE significance comparison between MSCALSTM and baseline models based on PeMSD4 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD4 dataset.…”
  6. 66

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD7 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD7 dataset.…”
  7. 67

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD3 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD3 dataset.…”
  8. 68

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD8 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD8 dataset.…”
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    Global Land Use Change Impacts on Soil Nitrogen Availability and Environmental Losses by Jing Wang (6206297)

    Published 2025
    “…In contrast, reversing managed to natural ecosystems significantly increased NNM by 20% (9.7, 25.4%) and decreased NN by 89% (−125, −46%), indicating increasing N availability while decreasing potential N loss. …”
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    Reduced (owner-animal metadata) XGBoost model on the <i>significant illness</i> binary using the primary decision-maker dataset. by Richard Barrett-Jolley (739341)

    Published 2024
    “…Acceptance threshold is indicated by the colour bar on the right-hand side, and also shown at discrete points on the curve. For example, with a threshold probability of 0.05, the model correctly predicts approximately 73% of dogs where the <i>significant illness</i> outcome was classified as ‘yes’, but the false-positive rate is approximately 45%. …”
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