Trees In Data Structures Presentation

Introduction to Trees in Data Structures
Trees are non-linear data structures that consist of nodes connected by edges. Each node can have zero or more child nodes, except for the root node. Trees are used to represent hierarchical relationships and organize data efficiently.	Image Source
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Types of Trees
Binary Trees: Each node can have at most two child nodes, known as the left child and the right child. Binary Search Trees: A type of binary tree in which the values of the left child are less than the parent node, and the values of the right child are greater. AVL Trees: Balanced binary search trees that maintain a balanced factor to ensure efficient search and insertion operations.	Image Source
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Operations on Trees
Insertion: Adding a new node to the tree in the appropriate position based on its value. Traversal: Visiting each node of the tree in a specific order, such as Inorder, Preorder, or Postorder traversal. Deletion: Removing a node from the tree while maintaining the integrity of the tree structure.	Image Source
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Applications of Trees
File Systems: Representing the directory structure of files and folders. Decision Trees: Used in machine learning for classification and regression problems. Huffman Trees: Efficiently encoding and decoding data, such as in file compression algorithms.	Image Source
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Conclusion
Trees are versatile data structures that allow for efficient organization and retrieval of data. Understanding different types of trees and their operations is essential for solving various problems. Further exploration and practice with trees can improve problem-solving skills in computer science.	Image Source
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References (download PPTX file for details)
Cormen, T. H., Leiserson, C. E., Rivest, R. L... Drozdek, A. (2005). Data Structures and Algor... Goodrich, M. T., Tamassia, R., & Goldwasser, ...
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