📌 K-Means Clustering
Click on the canvas to add data points, then run k-means to see how the algorithm clusters your data!
📈 Scree Plot (Elbow Method)
Shows total within-cluster sum of squares for different k values. Look for the "elbow" to find optimal k!
🌳 Hierarchical Clustering
Click to add points, then watch the dendrogram build as clusters merge!
Linkage Methods:
- Complete: Uses largest distance between any two points in clusters
- Single: Uses smallest distance between any two points in clusters
- Average: Uses average distance between all pairs of points
✂️ Cut the Tree: After building the dendrogram, use the slider to cut at different heights and see different cluster groupings! Points will be color-coded by cluster.
📊 Principal Component Analysis (PCA)
Click on the canvas to add data points or generate correlated data, then see how PCA finds the principal components!
📈 Scree Plot
Shows the percentage of variance explained by each principal component