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:
-
Applying K-means/DBSCAN/Agglomerative algorithms on a given data set
-
Choosing right value of k in K-means algorithm
-
Mapping of Data points per Cluster
-
Visualizing clustering output
-
Interpreting clustering output
-
Evaluate clustering output using SSE and Silhouette score
-
Analysing evaluating measures to decide final clustering output