k-Means and Choosing k
The elbow and silhouette methods.
The Go-To Clusterer
k-Means is the most popular clustering algorithm: it splits your data into k groups by grouping points around central anchors. 🎯
Centroids Are Anchors
Each cluster has a centroid, the mean position of its members. Points join the cluster whose centroid sits closest to them.
All lessons in this course
- Supervised vs Unsupervised
- k-Means and Choosing k
- Hierarchical and DBSCAN
- Profile and Name Your Clusters