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Explainable NMF Topic Model

Explainable NMF Topic Model ühendab mittenegatiivse maatriktuvastuse (Non-negative Matrix Factorization, NMF) – mis on dokument-termi maatriksi osadeks jaotamise meetod – eksplitsiitsete tõlgendatavuse tehnikatega, nagu koherentsusmeetrikad, sõnade panuse skoorid ja SHAP-laadsed atribuudid, et muuta avastatud teemad inimlugejatele läbipaistvaks ja auditeeritavaks.

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Allikad

  1. Lee, D. D., & Seung, H. S. (2001). Algorithms for non-negative matrix factorization. Advances in Neural Information Processing Systems, 13, 556–562. link
  2. Non-negative matrix factorization. Wikipedia. link

Kuidas sellele lehele viidata

ScholarGate. (2026, June 3). Explainable Non-negative Matrix Factorization Topic Model. ScholarGate. https://scholargate.app/et/deep-learning/explainable-nmf-topic-model

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ScholarGateExplainable NMF Topic Model (Explainable Non-negative Matrix Factorization Topic Model). Loetud 2026-06-15 aadressilt https://scholargate.app/et/deep-learning/explainable-nmf-topic-model · Andmestik: https://doi.org/10.5281/zenodo.20539026