k-means with selected initial centers

Question

I am trying to k-means clustering with selected initial centroids. It says here that to specify your initial centers:

init : {‘k-means++’, ‘random’ or an n         


        

Answer 1

The default behavior of KMeans is to initialize the algorithm multiple times using different random centroids (i.e. the Forgy method). The number of random initializations is then controlled by the n_init= parameter (docs):

n_init : int, default: 10

Number of time the k-means algorithm will be run with different centroid seeds. The final results will be the best output of n_init consecutive runs in terms of inertia.

If you pass an array as the init= argument then only a single initialization will be performed using the centroids explicitly specified in the array. You are getting a RuntimeWarning because you are still passing the default value of n_init=10 (here are the relevant lines of source code).

It's actually totally fine to ignore this warning, but you can make it go away completely by passing n_init=1 if your init= parameter is an array.