The first step to design a tree algorithm is to choose the right data structure to represent your tree. Depending on your problem, you may need a binary tree, a binary search tree, a trie, a heap ...

Learn how to balance accuracy and simplicity in your decision tree algorithm with tips and techniques on splitting, pruning, feature selection, visualization, and testing.

The automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. The ...

Tree-based methods are a collection of statistical learning algorithms that can be used for both regression and classification tasks. These methods divide the predictor space into regions and make ...

Decision-tree induction algorithms are widely used in machine learning applications in which the goal is to extract knowledge from data and present it in a graphically intuitive way. The most ...

Inclusive algorithm design. One way to achieve transparency is to involve community members in the process of algorithm design — something Rediet Abebe thinks is vital in her work.

This lesson covered minimum spanning tree algorithms, including Prim's and Kruskal's algorithms, along with their implementations. You also learned about their practical applications in networking, ...