Is it possible to specify your own distance function using scikit-learn K-Means Clustering?
Yes you can use a difference metric function; however, by definition, the k-means clustering algorithm relies on the eucldiean distance from the mean of each cluster. 
You could use a different metric, so even though you are still calculating the mean you could use something like the mahalnobis distance.
Is it possible to specify your own distance function using scikit-learn K-Means Clustering?