@thomaschampagne/naive-bayes

TypeScript Naive Bayes Classifier for Node and Browser

This "Naive Bayes Classifier" library is based on the bayes package. Library has been re-implemented as synchronous, refactored and cleaned under TypeScript, Jest, ESLint and Prettier.

What can I use this for?

You can use this for categorizing any text content into any arbitrary set of categories. For example:

• is an email spam, or not spam ?
• is a news article about technology, politics, or sports ?
• is a piece of text expressing positive emotions, or negative emotions?

Installing

npm install naive-bayes

Usage

import { NaiveBayes }  from "naive-bayes";

const classifier = new NaiveBayes();

// Teach it positive phrases
classifier.learn('amazing, awesome movie!! Yeah!! Oh boy.', 'positive');
classifier.learn('Sweet, this is incredibly, amazing, perfect, great!!', 'positive');

// Teach it a negative phrase
classifier.learn('terrible, shitty thing. Damn. Sucks!!', 'negative');

// Now ask it to categorize a document it has never seen before
console.log(classifier.categorize('awesome, cool, amazing!! Yay.')); // => 'positive'

// Serialize the classifier's state as a JSON string.
const model = classifier.toJson();

// Load the classifier back from its JSON representation.
const revivedClassifier = NaiveBayes.fromJson(model);

console.log(revivedClassifier.categorize('Damn')); // => 'negative'

API

const classifier = new NaiveBayes([options])

Returns an instance of a Naive-Bayes Classifier.

Pass in an optional options object to configure the instance. If you specify a tokenizer function in options, it will be used as the instance's tokenizer. It receives a (string) text argument - this is the string value that is passed in by you when you call .learn() or .categorize(). It must return an array of tokens. The default tokenizer removes punctuation and splits on spaces.

Eg.

const classifier = new NaiveBayes({
    tokenizer: text => { return text.split(' ') }
})

classifier.learn(text, category)

Teach your classifier what category the text belongs to. The more you teach your classifier, the more reliable it becomes. It will use what it has learned to identify new documents that it hasn't seen before.

classifier.categorize(text)

Returns the category it thinks text belongs to. Its judgement is based on what you have taught it with .learn().

classifier.toJson()

Returns the JSON representation of a classifier.

var classifier = NaiveBayes.fromJson(jsonStr)

Returns a classifier instance from the JSON representation. Use this with the JSON representation obtained from classifier.toJson()