Hierarchical Clustering
Hierarchical Clustering is one of the Unsupervised Learning
Steps:
- similar_ones = find 2 most similar
- Merge them together
- If length is greater than 1, go to Step 1
- For Step 1, we can use different metrics
- For step 2, we can use Average or Weighted Average or any other metrics
- In the final diagram, height gives the sense of similarity
- low height = most similar
- max height = lowest similarity