a$.$ Given a dataset and a value k$,$ let t vary from $0$ to a very large value. When does Leader Clustering produce more, the same number, or fewer clusters than k$-$means, assuming that the k initial centers are the same for both? When will the clusterings produced by Leader Clustering and k$-$means be identical?

b$.$ Which of the two methods, k$-$means or Leader Clustering, will be best at dealing with outliers $($data instances that are $$far away$$ or very different to the other instances in the dataset$)?$ Explain.