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Machine learningMachine learning

Aktiv læring stemmekomiteen

Active Learning Voting Ensemble — formelt kjent som Query by Committee — er en aktiv læringsstrategi som trener en komité av ulike modeller og velger de umerkede eksemplene der komitémedlemmene er mest uenige for menneskelig annotering. Ved å fokusere merkeinnsatsen på de mest informative punktene, oppnår den høy nøyaktighet med langt færre merkede eksempler enn passiv læring krever.

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Method map

The neighbourhood of related methods — select a node to explore.

Kilder

  1. Seung, H. S., Opper, M., & Sompolinsky, H. (1992). Query by committee. In Proceedings of the Fifth Annual Workshop on Computational Learning Theory (COLT '92), pp. 287–294. ACM. DOI: 10.1145/130385.130417
  2. Settles, B. (2009). Active Learning Literature Survey. Computer Sciences Technical Report 1648, University of Wisconsin–Madison. link

Slik siterer du denne siden

ScholarGate. (2026, June 3). Active Learning with Voting Ensemble (Query by Committee). ScholarGate. https://scholargate.app/no/machine-learning/active-learning-voting-ensemble

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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ScholarGateActive Learning Voting Ensemble (Active Learning with Voting Ensemble (Query by Committee)). Hentet 2026-06-15 fra https://scholargate.app/no/machine-learning/active-learning-voting-ensemble · Datasett: https://doi.org/10.5281/zenodo.20539026