Clustering Algorithms Unsupervised Learning Part-2
Unsupervised Algorithms Part-2 Clustering CLUSTER ANALYSIS – BASIC CONCEPTS In virtually every scientific field dealing with empirical data, people try to get a first impression on their data by trying to identify groups of “similar behavior” in their data. Consider you go to a supermarket, you will observe see how different items are grouped and arranged. They group and cluster items based on similarity. Clustering is one of the most widely used techniques for exploratory data analysis. Its applications range from statistics, computer science, biology to social sciences or psychology. Figure-1 Figure-2: Figure-3 Nature’s color cluster Here is another example. Let’s say you have a YouTube channel. Youtube may have a lot of data about the subscribers of your channel. You don’t need to tell the algorithm which group a subscriber belongs. The algorithm can find those connections without your help. For example, it may tell you that 35% of yo