Applying-Evaluating-Clustering-algorithms

This is a small tutorial project that demonstrates application and evaluation methods of popular clustering algorithms namely, K-means, DBSCAN and Agglomerative. The key learnings are:

1. Applying K-means/DBSCAN/Agglomerative algorithms on a given data set

2. Choosing right value of k in K-means algorithm

3. Mapping of Data points per Cluster

4. Visualizing clustering output

5. Interpreting clustering output

6. Evaluate clustering output using SSE and Silhouette score

7. Analysing evaluating measures to decide final clustering output