Showing 1 - 20 results of 5,329 for search '(((( learning data decrease ) OR ( a market decrease ))) OR ( i values decrease ))', query time: 0.53s Refine Results
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    The MAE value of the model under raw data. by Xiangjuan Liu (618000)

    Published 2025
    “…Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”
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    Three error values under raw data. by Xiangjuan Liu (618000)

    Published 2025
    “…Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”
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    The multiple criteria qualitative value-based pricing framework “MARIE” for new clinical status by Akina Takami (16407200)

    Published 2025
    “…However, the failure to incorporate a drug’s value when determining its price decreases pharmaceutical companies’ motivation to develop and launch novel drugs in Japan.…”
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    Estimation and prediction of the incidence <i>I</i>(<i>t</i>) in synthetic data. by Oscar Fajardo-Fontiveros (20469421)

    Published 2024
    “…For each of these scenarios, we consider four testing and reporting models (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012687#sec009" target="_blank">Methods</a> for details): constant reporting exponent <i>n</i> = −1 and testing that grows indefinitely with incidence (left column); constant reporting exponent <i>n</i> = −2 and testing that grows indefinitely with incidence (center-left column); variable reporting exponent <i>n</i> = −<i>α</i> log <i>C</i> and testing that grows indefinitely with incidence (center-right column); variable reporting exponent <i>n</i> = −<i>α</i> log <i>C</i> and testing that saturates at high incidence values (right column). …”
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