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Regularized Naive Bayes

Regularized Naive Bayes augments the classical Naive Bayes probabilistic classifier with explicit smoothing or shrinkage — most commonly Laplace (additive) smoothing — to prevent zero-probability estimates for unseen feature values and to reduce overfitting. The result is a fast, robust classifier that generalizes better than unsmoothed Naive Bayes, particularly on sparse or high-dimensional data such as text.

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Regularized Naive Bayes Classifier

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

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