Clustering Based Unsupervised Learning – Towards Data Science

Unsupervised machine learning is the machine learning task of inferring a function to describe hidden structure from "unlabeled" data (a classification or categorization is not included in the observations). While there is an exhaustive list of clustering algorithms available (whether you use R or Python's Scikit-Learn), I will attempt to cover the basic concepts. The most common and simplest clustering algorithm out there is the K-Means clustering. This algorithms involve you telling the algorithms how many possible cluster (or K) there are in the dataset. The algorithm then iteratively moves the k-centers and selects the datapoints that are closest to that centroid in the cluster.