ML:Hierarchical Agglomerative Clustering and K-means Clustering

In this assignment, I implemented the two types of clustering methods, Lloyd’s algorithm (“k-means”) and hierarchical agglomerative clustering, on two datasets, to compare their clustering results.

• K-means Clustering: applied two different initialization methods(uniform random and k-means++) and implemented the k-means clustering from scratch.

• Hierarchical Agglomerative Clustering: used two dissimilarity measures between clusters(single linkage and average linkage) to implement the hierarchical clustering with skilearn.

Plots of Clustering Results

Dataset 1 K-means

Dataset 2 using K-means

Dataset 1 using hierarchical

Dataset 2 using hierarchical