K-Means-Clustering

Tasks

• Take input from the given source data file and plot all the points.
• Perform the k-means clustering algorithm applying Euclidean distance as a distance measure on the given dataset with k=2. Take random points from the given data as initial centroids.
• Color the corresponding points on the clusters with different colors.