K-mean Clustering

How does K-mean clustering works?

  1. Choose the number of K clusters.
  2. Select at random K points, the centroid.
  3. Assign each data point to the closest centroid. That forms K clusters.
  4. Compute and place the new centroid of each cluster.
  5. Reassign each data point to the new closest centroid. If any reassignment takes place go to step 4 otherwise your model is ready.

How to choose the right value for K

Elbow Method

Use cases of K mean in Security Domain

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store