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Semi-superviseret K-Nærmeste Naboer

Semi-superviseret KNN udvider den klassiske K-nærmeste naboer-algoritme til at udnytte store mængder uannoterede data sammen med et lille annoteret datasæt. Ved at opbygge en KNN-graf over alle observationer og udbrede kendte labels gennem grafens kanter, udleder metoden labels for uannoterede punkter uden at kræve dyr manuel annotering af hver prøve.

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Kilder

  1. Zhu, X. & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University. link
  2. Chapelle, O., Scholkopf, B. & Zien, A. (Eds.) (2006). Semi-Supervised Learning. MIT Press. ISBN: 978-0-262-03358-9

Sådan citerer du denne side

ScholarGate. (2026, June 3). Semi-supervised K-Nearest Neighbors (Label Propagation via KNN Graph). ScholarGate. https://scholargate.app/da/machine-learning/semi-supervised-k-nearest-neighbors

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Refereret af

ScholarGateSemi-supervised K-nearest neighbors (Semi-supervised K-Nearest Neighbors (Label Propagation via KNN Graph)). Hentet 2026-06-15 fra https://scholargate.app/da/machine-learning/semi-supervised-k-nearest-neighbors · Datasæt: https://doi.org/10.5281/zenodo.20539026