3 Hierarchical Clustering Techniques: Concepts and Examples

Learn how hierarchical clustering works and its applications in data analysis. This lesson explores clustering fundamentals, different linkage criteria, and practical examples to understand hierarchical clustering techniques in depth.
Introduction to hierarchical clustering and its importance
Difference between agglomerative and divisive methods
Explanation of dendrograms and interpretation
Step-by-step walkthrough of linkage criteria (single, complete, average)
Pros and cons of hierarchical clustering
Real-world examples using sample datasets
Challenges and best practices in implementation
Comparison with other clustering algorithms like k-means
#Clustering #MachineLearning #DataScience