• Project (Description): Binary Tree Visualization using OpenGL.
• Synopsis: This project was inspired by the need to visualize decision [binary] trees. In the domain of machine learning, some decision trees make a binary split of the data. The decision tree is one of the most commonly used classification techniques. One of the best things about decision trees is that humans can easily understand the data. The decision tree does a great job of distilling data into knowledge. With this, you can take a set of unfamiliar data and extract a set of rules. The machine learning will take place as the machine creates these rules from the dataset. Decision trees are often used in expert systems, and the results obtained by using them are often comparable to those from a human expert with decades of experience in a given field.
• Objectives: a) Creation and visualization of binary trees. b) Balancing the tree. c) Creation of tree mask and map matrices for a tree. d) Deleting nodes and Inserting back sub [binary] trees.
• Programming Languages and IDEs: a) C and C++ Data Structures & Algorithms. b) OpenGL API. c) Microsoft Visual Studio IDE.
• How to use: bsTree.cpp defines the entry point for the application. In this file, create and populate your BinarySearchTree class object in the function: populateTree(), and you are ready to compile and run the program. When your tree previews initially and you do not like its structure, you can press keyboard letter ‘v’ to balance the tree. The balanced tree will then replace the initially created tree and will preview in its stead.
• Feedback: Please send me an email at: emmanuel.c.chidinma@gmail.com