Decision tree in machine learning: Learn how to use decision

Learn how to use decision trees to classify or predict outcomes based on a set of rules. See examples, types, implementation, and assumptions of the algorithm. A Decision Tree helps us to make decisions by mapping out different choices and their possible outcomes. It’s used in machine learning for tasks like classification and prediction. In this article, we’ll see more about Decision Trees , their types and other core concepts. Decision trees stand as one of the most intuitive and widely-used algorithms in machine learning . Unlike black-box models that obscure their reasoning, decision trees mirror human decision-making processes, making them accessible to both technical and non-technical audiences. This transparency, combined with their versatility in handling both classification and regression tasks, has cemented their position as a fundamental tool in the data scientist’s arsenal. What is a Decision Tree ? A ... Learn all about decision trees in machine learning , including types, working, Python implementation, pruning, and tuning for better predictions.