Tracing Covid-19

 

1. Density-based Clustering: Clusters are formed based on the density of the region — examples of this type: DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and OPTICS (Ordering Points to Identify Clustering Structure).
2. Hierarchal-based Clustering: Clusters are formed using a tree-type structure. Some clusters are predefined and then used to create new clusters — examples of this type: CURE (Clustering Using Representatives), BIRCH (Balanced Iterative Reducing Clustering, and using Hierarchies).
3. Partitioning-based Clustering: Clusters are formed by partitioning the input data into k clusters — examples of this type: K-means, CLARANS 
4.  (Clustering Large Applications based upon Randomized Search).
5. Mock Data Generator
   
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