Natural NPM Package - Decision Tree Classifier

Decision Trees are a popular machine learning algorithm used in the natural npm package for text classification tasks. In the natural module, the DecisionTreeClassifier class provides an implementation of this algorithm.

Here is an example of how to use DecisionTreeClassifier to classify text:

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

// 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 DecisionTreeClassifier 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 DecisionTreeClassifier instance to classify new text into one of the previously defined categories.

The DecisionTreeClassifier class also provides various other methods for working with decision trees, such as prune for reducing the complexity of the tree and save/load for persisting the trained model to disk.