Random Forest Classification

Background information & sample use case in 7 minutes

Machine learning models are usually broken down into supervised and unsupervised learning algorithms. Supervised models are created when we have defined (labeled) parameters, both dependent and independent. Conversely, unsupervised methods are used when we don’t have defined (unlabeled) parameters. For this article we will focus on a specific supervised model, known as Random Forest, and will demonstrate a basic use case on Titanic survivor data. …

ai classification data science machine learning random random-forest supervised learning