Today i'm trying to learn something about K-means. I Have understand the algorithm and i know how it works. Now i'm looking for the right k... I found the elbow criterion as a method to detect the right k but i do not understand how to use it with scikit learn?! In scikit learn i'm clustering things in this way

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

So should i do this several times for n_clusters = 1...n and watch at the Error rate to get the right k ? think this would be stupid and would take a lot of time?!