Machine learningDeep learning / NLP / CV

Objašnjivi NMF model tema

Objašnjivi NMF model tema kombinira NMF (Non-negative Matrix Factorization) – dekompoziciju matrice dokumenata i pojmova na faktore temeljene na dijelovima – s eksplicitnim tehnikama interpretativnosti kao što su metrike koherentnosti, rezultati doprinosa riječi i SHAP-stilski atributi kako bi otkrivene teme bile transparentne i provjerljive za ljudske čitatelje.

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Izvori

  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

Kako citirati ovu stranicu

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

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ScholarGateExplainable NMF Topic Model (Explainable Non-negative Matrix Factorization Topic Model). Preuzeto 2026-06-15 s https://scholargate.app/hr/deep-learning/explainable-nmf-topic-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026