You have to do following thing:
1.You are required to write a program which implements K-Means algorithm.
2.Program should be able to take random instances as initial seeds.
3.Value of K must be user-defined.
4.Experiment with both Euclidian distance and Manhattan distance.
5.You may use Iris dataset for clustering.
6.Program should be able to handle any user provided continuous dataset.
7.Provide an analysis of final clusters created by Euclidian and Manhattan metrics.