পদ্ধতির তুলনা করুন

	অনলাইন গাউসিয়ান মিক্সচার মডেল	বেয়েশীয় গাউসীয় মিশ্রণ মডেল (Bayesian Gaussian Mixture Model)
ক্ষেত্র	যন্ত্র শিখন	যন্ত্র শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2000–2009	1999–2006
প্রবর্তক	Cappé, O. & Moulines, E. (online EM formulation)	Attias, H.; Bishop, C. M.
ধরন	Probabilistic clustering / density estimation (incremental)	Probabilistic clustering / density estimation
মৌলিক উৎস	Cappé, O. & Moulines, E. (2009). On-line expectation-maximization algorithm for latent data models. Journal of the Royal Statistical Society: Series B, 71(3), 593–613.	Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Ch. 10). Springer. ISBN: 978-0-387-31073-2
অপর নাম	Online GMM, Incremental GMM, Streaming Gaussian Mixture Model, Sequential GMM	Bayesian GMM, Variational Gaussian Mixture, VBGMM, Dirichlet Process Gaussian Mixture
সম্পর্কিত	5	4
সারসংক্ষেপ	Online Gaussian Mixture Model adapts the classic GMM to streaming or large-scale data by replacing full-batch EM with incremental updates — processing one observation or mini-batch at a time and continuously refining component means, covariances, and mixing weights without revisiting the entire dataset.	The Bayesian Gaussian Mixture Model places prior distributions over all mixture parameters and infers their posteriors — typically via Variational Bayes or MCMC — rather than fitting fixed point estimates. This yields principled uncertainty quantification, automatic selection of the effective number of components, and resistance to overfitting small datasets.