From the course: Machine Learning and AI Foundations: Decision Trees with KNIME

The basics of decision trees - KNIME Tutorial

From the course: Machine Learning and AI Foundations: Decision Trees with KNIME

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The basics of decision trees

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- [Keith] If you are interested in data science and machine learning, decision trees are one of the most foundational topics of all. They have been in widespread use for many years. So they represent a topic that as data professionals, we are expected to be familiar with. Just as important, learning about them is a critical first step to understand more complex techniques like XGBoost and Random Forests. Hi, I'm Keith McCormick, and decision trees have been among the techniques that I've used throughout my career. Even when I haven't deployed a decision tree model as a final solution, it has often played an important role in my analysis. We'll focus on the basics in this course. We will be using the nine analytics platform for demonstration purposes, but we will be focused on the concepts. In particular, we will be exploring three of the most widely known and adopted decision tree algorithms, C4.5, classification trees, and regression trees. You will be able to apply the concepts to any platform whether it be R or Python or another analytics workbench. So this is a course for all data scientists that are interested in decision trees. We have a lot to cover, so let's get started.

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