Showing 9,201 - 9,220 results of 48,561 for search '(( a ((mean decrease) OR (linear decrease)) ) OR ( a ((greatest decrease) OR (largest decrease)) ))', query time: 0.75s Refine Results
  1. 9201

    List of datasets in AqSolDB. by Bin Pan (742525)

    Published 2025
    “…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
  2. 9202

    Feature importance derived from SHAP analysis. by Bin Pan (742525)

    Published 2025
    “…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
  3. 9203
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    DataSheet1_Decreasing incidence and mortality of lung cancer in Hungary between 2011 and 2021 revealed by robust estimates reconciling multiple data sources.ZIP by Gabriella Gálffy (177759)

    Published 2024
    “…The COVID-19 pandemic resulted in a statistically significant decrease in lung cancer incidence, especially in the 50–59 age group (both sexes).…”
  8. 9208

    Image_3_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.TIF by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
  9. 9209

    Image_1_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.TIF by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
  10. 9210

    Table_2_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.CSV by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
  11. 9211

    Image_2_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.TIF by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
  12. 9212

    Table_1_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.XLSX by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
  13. 9213

    Table_3_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.xlsx by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
  14. 9214

    Table_4_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.xlsx by Iulian Gabur (11720927)

    Published 2022
    “…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”
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