Machine learning calibration of low-cost no and pm sensors: non-linear algorithms and their impact on site transferability

HIGHLIGHTS

• who: Atmos. Meas. Tech. et al. from the Institute, Climate Change and the Environment, Imperial College London, London , AZ, UK , Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich , TJ, UK have published the research: Machine learning calibration of low-cost NO and PM sensors: non-linear algorithms and their impact on site transferability, in the Journal: (JOURNAL) of 30/04/2020
• what: The authors compare the performance of ridge regression a linear statistical learning algorithm to two non-linear algorithms in the form of random forest regression (RFR) and Gaussian process . . .
  

   

  

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