Showing 1 - 20 results of 7,282 for search '(((( training data decrease ) OR ( _ larger decrease ))) OR ( _ values decrease ))', query time: 0.63s Refine Results
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    The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. by Gui Araujo (22170819)

    Published 2025
    “…Each sample is a simulation of the entire assembly process for a scenario. Parameter values: interaction strengths were drawn from a half-normal distribution of zero mean and a standard deviation of 0.2, and strength for consumers was made no larger than the strength for resources. …”
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    Scheme of g-λ model with larger values λ. by Zhanfeng Fan (20390992)

    Published 2024
    “…And if the value of λ assumes larger values, the distortion in the shape of the transmitted wave is associated with the plastic deformation in the uncoupled rock mass. …”
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    Biases in larger populations. by Sander W. Keemink (21253563)

    Published 2025
    “…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. Bias decreases with increasing neurons in the population. …”
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    (A) Network map of the top ten anti-AD core targets and the top 30 KEGG pathways. The color of the pathway nodes changed from pink to light pink as the DC value decreased. (B) 19 core pathways with DC values (ranked by DC>  average value of (4.933)). by Shakeel Ahmad Khan (13202394)

    Published 2025
    “…The color of the pathway nodes changed from pink to light pink as the DC value decreased. (B) 19 core pathways with DC values (ranked by DC>  average value of (4.933)).…”
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    Paeameter ranges and optimal values. by Zhen Zhao (159931)

    Published 2025
    “…Subsequently, the feature factors corresponding to the model with the highest accuracy were selected as the optimal feature subsets and used in the model construction as input data. Additionally, considering the imbalanced in population spatial distribution, we used the K-means ++ clustering algorithm to cluster the optimal feature subset, and we used the bootstrap sampling method to extract the same amount of data from each cluster and fuse it with the training subset to build an improved random forest model. …”