A decision tree is a useful machine learning algorithm used for both regression and classification tasks. The name "decision tree" comes from the fact that the algorithm keeps dividing the dataset down into smaller and smaller portions until the data has been divided into single instances, which are then classified. If you were to visualize the results of the algorithm, the way the categories are divided would resemble a tree and many leaves. That's a quick definition of a decision tree, but let's take a deep dive into how decision trees work. Having a better understanding of how decision trees operate, as well as their use cases, will assist you in knowing when to utilize them during your machine learning projects.
Oct-27-2019, 12:37:14 GMT