What Is A Decision Tree In Machine Learning?

Decision trees are a type of supervised learning algorithm used for both classification and regression tasks. They are a flexible tool for most decision-making applications and can be used for single applications or to score entire portfolios of consumers quickly and automatically. There are two main types of decision trees: classification and regression, and many subcategories with customizable settings. Popular decision tree algorithms include CART and C4.5, and there are many free and commercial software packages that offer various settings and types of algorithms. Combinations of decision trees, such as random forests and gradient boosting machines, are also popular machine learning algorithms.