## kmeans clustering algorithm

Do you have observed data?

You can **cluster it automatically** with the **kmeans algorithm**.

In the kmeans algorithm, __k is the number of clusters__.

Clustering is an _unsupervised machine learning task. _ Everything is automatic.

**Related course:** Data Science and Machine Learning with Python – Hands On!

### kmeans data

We always start with data. This is our observed data, simply a list of values.

We plot all of the observed data in a scatter plot.

# clustering dataset |

Result:

### kmeans clustering example

We will cluster the observations automatically.

K can be determined using the elbow method, but in this example we’ll set K ourselves.

**Note:**K is always a positive integer. We cannot have -1 clusters (k).

The k-means clustering algorithms goal is to partition observations into k clusters.

Each *observation belong to the cluster with the nearest mean.*

# clustering dataset |

Result:

If you see the above result, Kmeans has clustered the observations automatically.