Browsing Sentraladministrasjonen by Subject "Data streams"

Now showing items 1-2 of 2

    • Estimating tukey depth using incremental quantile estimators 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Pattern Recognition;Volume 122, February 2022, 108339, Peer reviewed; Journal article, 2022)
      Measures of distance or how data points are positioned relative to each other are fundamental in pattern recognition. The concept of depth measures how deep an arbitrary point is positioned in a dataset, and is an interesting ...

    • Joint tracking of multiple quantiles through conditional quantiles 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Information Sciences;Volume 563, July 2021, Peer reviewed; Journal article, 2021-03-05)
      The estimation of quantiles is one of the most fundamental data mining tasks. As most real-time data streams vary dynamically over time, there is a quest for adaptive quantile estimators. The most well-known type of adaptive ...