4 Matching Annotations
  1. Last 7 days
    1. Each cell shows how often a given curve fit is not significantly worse than the fit with the best cross-validation accuracy.

      研究使用交叉验证来评估不同曲线拟合的优劣,每个单元格显示给定曲线拟合与最佳拟合相比不显著差于的频率。这种方法提供了更稳健的统计评估,减少了过拟合风险。

  2. Jul 2020
  3. Apr 2020
  4. May 2018
    1. Negative values included when assessing air quality In computing average pollutant concentrations, EPA includes recorded values that are below zero. EPA advised that this is consistent with NEPM AAQ procedures. Logically, however, the lowest possible value for air pollutant concentrations is zero. Either it is present, even if in very small amounts, or it is not. Negative values are an artefact of the measurement and recording process. Leaving negative values in the data introduces a negative bias, which potentially under represents actual concentrations of pollutants. We noted a considerable number of negative values recorded. For example, in 2016, negative values comprised 5.3 per cent of recorded hourly PM2.5 values, and 1.3 per cent of hourly PM10 values. When we excluded negative values from the calculation of one‐day averages, there were five more exceedance days for PM2.5 and one more for PM10 during 2016.