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:

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.

Result:
kmeans dataset

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.

Result:
kmeans clustering algorithm

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

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