# http://stackoverflow.com/questions/6645895/calculating-the-percentage-of-variance-measure-for-k-means

cents = [km.kmeans.cluster_centers_ for km in kms]
D_k = [cdist(rid_brand_pca, cent, 'euclidean') for cent in cents]

# 最も近い中心との距離
dist = [np.min(D,axis=1) for D in D_k]
avgWithinSS = [sum(d)/rid_brand_pca.shape[0] for d in dist]

# elbow curve
K = range(1, 16)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(K, avgWithinSS, 'b*-')

plt.grid(True)
plt.xlabel('Number of clusters')
plt.ylim((1.6, 2.0))
plt.ylabel('Average within-cluster sum of squares')
plt.title('Elbow for KMeans clustering')