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A Comparison of Methods for Automatic Outlier Detection in Ergospirometric Data and Their Effect on the Performance of Predictive Models

  • Baumgartner N
  • Kranzinger C
  • Kranzinger S
  • et al.
DOI: 10.1007/978-3-031-31772-9_12
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Abstract

Features obtained from cardiopulmonary exercise testing provide useful information for predicting target values of high interest in the sports and healthcare industry. However, these sensor-generated data are susceptible to different factors that may cause imprecise...

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Baumgartner, N., Kranzinger, C., Kranzinger, S., Snyder, C., Stöggl, T., & Resch, B. (2023). A Comparison of Methods for Automatic Outlier Detection in Ergospirometric Data and Their Effect on the Performance of Predictive Models (pp. 55–59). https://doi.org/10.1007/978-3-031-31772-9_12

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