add labels to sklearn k-means

Question

I am trying to use kmeans in python.

data = [[1,2,3,4,5],[1,0,3,2,4],[4,3,234,5,5],[23,4,5,1,4],[23,5,2,3,5]]

Each of this data have a label. Example:

[1,2,3,4,5] -> Fiat1
[1,0,3,2,4] -> Fiat2
[4,3,234,5,5] -> Mercedes
[23,4,5,1,4] -> Opel
[23,5,2,3,5] -> bmw

kmeans = KMeans(init='k-means++', n_clusters=3, n_init=10)
kmeans.fit(data)

My objective is after I run the KMeans, I want to obtain the labels of each cluster.

A fake example:

Cluster 1: Fiat1, Fiat2

Cluster 2: Mercedes

Cluster 3: bmw, Opel

How can I do that ?

Answer 1

Code

from sklearn.cluster import KMeans
import numpy as np

data = np.array([[1,2,3,4,5],[1,0,3,2,4],[4,3,234,5,5],[23,4,5,1,4],[23,5,2,3,5]])
labels = np.array(['Fiat1', 'Fiat2', 'Mercedes', 'Opel', 'BMW'])
N_CLUSTERS = 3

kmeans = KMeans(init='k-means++', n_clusters=N_CLUSTERS, n_init=10)
kmeans.fit(data)
pred_classes = kmeans.predict(data)

for cluster in range(N_CLUSTERS):
    print('cluster: ', cluster)
    print(labels[np.where(pred_classes == cluster)])

Output:

cluster:  0
['Opel' 'BMW']
cluster:  1
['Mercedes']
cluster:  2
['Fiat1' 'Fiat2']