Natural NPM Package - NLP Classification

Naive Bayes Classifier

const natural = require('natural');
const classifier = new natural.BayesClassifier();

// Train the classifier with some sample data
classifier.addDocument('I am feeling happy today.', 'positive');
classifier.addDocument('This movie is boring and dull.', 'negative');
classifier.addDocument('The weather is beautiful outside.', 'positive');
classifier.addDocument('I hate Mondays.', 'negative');
classifier.train();

// Classify some new text
const result1 = classifier.classify('I love this book!');
const result2 = classifier.classify('The food at this restaurant is terrible.');
console.log(result1); // Output: positive
console.log(result2); // Output: negative

In this example, we first create a BayesClassifier instance and train it with some sample data using the addDocument method. We then call the train method to train the classifier on the data.

We can then use the classify method of the BayesClassifier instance to classify new text into one of the previously defined categories.

Logistic Regression Classifier:

const natural = require('natural');
const classifier = new natural.LogisticRegressionClassifier();

// Train the classifier with some sample data
classifier.addDocument('I am feeling happy today.', 'positive');
classifier.addDocument('This movie is boring and dull.', 'negative');
classifier.addDocument('The weather is beautiful outside.', 'positive');
classifier.addDocument('I hate Mondays.', 'negative');
classifier.train();

// Classify some new text
const result1 = classifier.classify('I love this book!');
const result2 = classifier.classify('The food at this restaurant is terrible.');
console.log(result1); // Output: positive
console.log(result2); // Output: negative

This example is similar to the previous one, but uses the LogisticRegressionClassifier instead of the BayesClassifier. The usage is similar to the previous example.

Note that the natural module provides various other approaches to NLP classification, such as Support Vector Machines (SVM) and Decision Trees, which can be used in a similar way. The choice of classifier algorithm depends on the specific use case and the nature of the data.