k-mean-clustering

Applying k-mean clustering on a dataset using R. You are required to apply k-mean clustering on the dataset. You have to go through these steps. • Import dataset o You need to understand this dataset and know what it needs to be clustered. o Extract your features from the data. o Make estimation about what you need to cluster and what these data tells you how samples do you have etc. • Pre-processing o Your dataset needs to be ready for the training step. So you need to filter your necessary information. o Normalizing your data is necessary in this step. (if you have picked up a data that is already normalized then you will get this step points) • Training the model o What is your suitable k according to your problem? • Evaluate your model o What are your clusters and their centres? o What is your error function? Manhattan distance or Euclidian distance o Plot your clusters o Justify what is the meaning of these clusters according to your problem?