Bayes.BernoulliNB

Bernoulli Naive Bayes classifier for binary or boolean features. Continuous features can be converted to binary values using the binarize threshold. Class and feature probabilities are estimated with additive smoothing.

interface BernoulliNBProps {
    alpha?: number;
    binarize?: number | null;
    fitPrior?: boolean;
    classPrior?: number[] | null;
}
constructor(props: BernoulliNBProps = {})

Parameters

• alpha — Additive smoothing parameter applied when estimating probabilities. Defaults to 1.0.
• binarize — Threshold for binarizing input features. If null, the input is assumed to already be binary.
• fitPrior — Whether to learn class prior probabilities from the training data. When false, a uniform prior is used.
• classPrior — Optional array of prior probabilities for each class. If provided, these values override the learned priors.

Example

const clf = new BernoulliNB();
clf.fit(trainX, trainY);
const result = clf.predict(testX);