The following are some of the primary advantages of ID3: The training data is used to generate understandable prediction rules. Builds a short tree in a short amount of time. It simply needs to test a small number of attributes until all of the data has been categorised.
In the shape of a tree structure, a decision tree constructs classification or regression models. It incrementally cuts down a dataset into smaller and smaller sections while also developing an associated decision tree. Both category and numerical data can be handled by decision trees.