Data Science and Business Analytics Task-2
AIM : From the given IRIS dataset, predict the optimum number of clusters and represent it visually.
Tool(s) Used - Python
The clustering algorithm used is K-Means Clustering
K-means clustering is a common example of an exclusive clustering method where data points are assigned into K groups, where K represents the number of clusters based on the distance from each group’s centroid. The data points closest to a given centroid will be clustered under the same category. A larger K value will be indicative of smaller groupings with more granularity whereas a smaller K value will have larger groupings and less granularity.