An initial investigation: K-Means and Bisecting K-Means Algorithms for Clustering

Clustering is a class of Machine Learning Algorithms that looks to determine for clusters that represent similarity between groups of related data they each hold. While it is technically an Unsupervised type algorithm, in that it does not predict for a target variable, its application results in taking data that you might hypothesize has clusters that can categorize groups of related data, and forming clusters that represent data that have similarities. Thus, the effect of Clustering Algorithms could be viewed with the same effect as that of Classification Algorithms (a class type Supervised Algorithm). There are of course a number of type clustering algorithms, one being the K-Means Clustering Algorithm. The algorithm is shown as below.