In this article, we'll describe different methods for determining the optimal number of clusters for k-means, k-medoids (PAM) and hierarchical clustering.
a) Estimation of the optimal number of clusters using the elbow
How to determine the optimal number of clusters: scree plots and
5 Amazing Types of Clustering Methods You Should Know - Datanovia
MAKE, Free Full-Text
Unsupervised machine learning - Articles - STHDA
How to find the number of clusters using elbow method without
Applying K-means Clustering Model to Customer Segmentation, by Lisa
So You Have Some Clusters, Now What?
Sustainability, Free Full-Text
Evaluation of Classification Models: Confusion Matrix, ROC , AUC ,Gains ,and Lift Charts
Exploring Clustering Algorithms: Explanation and Use Cases
Cluster Validation Statistics: Must Know Methods - Datanovia
Chapter 20 K Means 381M Course Tutorials
clustering - Elbow Method for optimal no. of clusters - Data
:format(webp)/https://static-hk.zacdn.com/p/dagi-5647-1625436-1.jpg)
