Rekodi ya ushahidi wa mbinu

Bayesian Naive Bayes

Bayesian Naive Bayes applies a fully Bayesian treatment to the parameters of the classic Naive Bayes classifier: instead of estimating class-conditional distributions by maximum likelihood, it places conjugate priors (typically Dirichlet for categorical data or Gaussian-Gamma for continuous data) over the parameters and integrates them out, producing predictive posterior distributions that naturally quantify uncertainty and avoid overfitting on small datasets.

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Fully Bayesian Naive Bayes Classifier

Rekodi ya mbinu ya kiajenda · ml-model / machine-learning

Murphy, K. P. (2012). Machine Learning: A Probabilistic Perspective (Ch. 3, 4). MIT Press. · ISBN 978-0-262-01802-9
Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Ch. 8). Springer. · ISBN 978-0-387-31073-2

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