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sklearn.naive_bayes.MultinomialNB

sklearn.naive_bayes.MultinomialNB

Visibility: public Uploaded 13-08-2021 by Sergey Redyuk sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 2 runs
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  • openml-python python scikit-learn sklearn sklearn_0.18.1
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Naive Bayes classifier for multinomial models The multinomial Naive Bayes classifier is suitable for classification with discrete features (e.g., word counts for text classification). The multinomial distribution normally requires integer feature counts. However, in practice, fractional counts such as tf-idf may also work.

Parameters

alphaAdditive (Laplace/Lidstone) smoothing parameter (0 for no smoothing)default: 1.0
class_priorPrior probabilities of the classes. If specified the priors are not adjusted according to the data.default: null
fit_priorWhether to learn class prior probabilities or not If false, a uniform prior will be useddefault: true

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