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Uainishaji wa K-means unaozingatia nadharia ya Bayes (Bayesian K-means Clustering)

Uainishaji wa K-means unaozingatia nadharia ya Bayes huupanua mbinu ya kawaida ya K-means kwa kuweka usambazaji wa awali (prior distributions) juu ya vituo vya makundi (cluster centroids) na uwiano wa mchanganyiko. mfumo huu wa uwezekano hutoa makadirio ya kutokuwa na uhakika kwa mgawo wa makundi, huruhusu uchaguzi wa kimaumbile wa idadi ya makundi, na hurekebisha makadirio ya vituo—hasa muhimu wakati data ni chache au ina vipimo vingi.

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Vyanzo

  1. Kulis, B. & Jordan, M. I. (2012). Revisiting k-means: New algorithms via Bayesian nonparametrics. In Proceedings of the 29th International Conference on Machine Learning (ICML), Edinburgh, Scotland, pp. 513–520. link
  2. Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer. Chapter 9 (Mixture models and EM) and Chapter 10 (Approximate Inference). ISBN: 978-0387310732

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Bayesian K-means Clustering. ScholarGate. https://scholargate.app/sw/statistics/bayesian-k-means-clustering

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ScholarGateBayesian K-means clustering (Bayesian K-means Clustering). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/statistics/bayesian-k-means-clustering · Seti ya data: https://doi.org/10.5281/zenodo.20539026