3 Greedy Algorithms for Decision Trees, Explained with Examples

The article explains the fundamental principles behind decision trees, emphasizing their construction through greedy algorithms that iteratively select the most informative splits. It provides detailed examples to illustrate how these algorithms optimize decision boundaries by maximizing information gain or minimizing impurity at each node, enhancing understanding of their inner workings and practical implementation in data science.