GitHub - RiteshopShrivastava/Hierarchical_Clustering: Unsupervised-ML---K-Means-Clustering-Non-Hierarchical-Clustering-Univ. Use Elbow Graph to find optimum number of clusters (K value) from K values range. The K-means algorithm aims to choose centroids that minimise the inertia, or within-cluster sum-of-squares criterion WCSS. Plot K values range vs WCSS to get Elbow graph for choosing K (no. of clusters)

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
Assignment_Q1_Clustering.ipynb		Assignment_Q1_Clustering.ipynb
Hierarchical_clustering.ipynb		Hierarchical_clustering.ipynb
Universities_Clustering.csv		Universities_Clustering.csv

About

Unsupervised-ML---K-Means-Clustering-Non-Hierarchical-Clustering-Univ. Use Elbow Graph to find optimum number of clusters (K value) from K values range. The K-means algorithm aims to choose centroids that minimise the inertia, or within-cluster sum-of-squares criterion WCSS. Plot K values range vs WCSS to get Elbow graph for choosing K (no. of c…