Short Kmeans Example from Sklearn

Kmeans algorithm (python)

from sklearn.cluster import KMeans

K=3 # number of clusers

# setting random_state to 0 seeds random number generate to get
# the same results every run. X is the a MxN matrix where N is the number of features
# and M is the number of examples. 
kmeans = KMeans(n_clusters=K, random_state=0).fit(X)

# location of centroids
centroids = kmeans.cluster_centers_ 

# labels for each example, an Mx1 matrix
idx = kmeans.labels_