Cluster Evaluation Metrics and Interpretation_training
Автор: Mathew K Analytics
Загружено: 2025-10-15
Просмотров: 44
Описание:
Explore key methods for evaluating the quality of clustering results and learn how to interpret them effectively. This session provides practical guidance on cluster analysis using Python and essential clustering evaluation metrics.
Overview of internal and external cluster evaluation metrics
Detailed explanation of Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index
Discussion of ground truth labels and external validation
How to interpret clustering results in unsupervised learning
Demonstrating metric calculations using sample data
Limitations and common pitfalls in cluster evaluation
Practical tips for selecting the right metrics
Application of evaluation metrics in real-world data science workflows
#Clustering #DataScience #MachineLearning
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