I have used the following k mediod algo. as given in lec slides.

Following is the K mediod algorithm.

1. Initialize: randomly select k of the n data points as the mediods
2. Associate each data point to the closest medoid
3. For each mediod m
   1. For each non-mediod data point o
      1. Swap m and o and compute the total cost of the configuration
4. Select the configuration with the lowest cost.
5. repeat steps 2 to 5 until there is no change in the medoid.              Answer is same but approach is different