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sklearn.naive_bayes.BernoulliNB

sklearn.naive_bayes.BernoulliNB

Visibility: public Uploaded 13-12-2019 by Evan Peterson sklearn==0.22 numpy>=1.6.1 scipy>=0.9 0 runs
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  • openml-python python scikit-learn sklearn sklearn_0.22
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Naive Bayes classifier for multivariate Bernoulli models. Like MultinomialNB, this classifier is suitable for discrete data. The difference is that while MultinomialNB works with occurrence counts, BernoulliNB is designed for binary/boolean features.

Parameters

alphaAdditive (Laplace/Lidstone) smoothing parameter (0 for no smoothing)default: 1.0
binarizeThreshold for binarizing (mapping to booleans) of sample features If None, input is presumed to already consist of binary vectorsdefault: 0.0
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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