"No one is harder on a talented person than the person themselves" - Linda Wilkinson ; "Trust your guts and don't follow the herd" ; "Validate direction not destination" ;

November 08, 2015

K Means Clustering


I'm slowly moving in Stats with a lot of learning. This post is from my class notes

K-means clustering

  • Finding groups of object similar to one another
  • Partitioning cluster approach
  • Mean moves every time (Within first few iterations it will converge)
  • Classify a given data set through a certain number of clusters
  • This does not fit well for Sparse / Dense clusters

Great 5 Minute Video



Step 1 - "Figure out centric of region"
Step 2 - "Select K Data points randomly"
Step 3 - "Assign each data point to nearest centre"
Step 4 - "Recalculate the new centroids"
Step 5 - "Repeat Step 3,4"

More Reads - K-Means Clustering

Happy Learning!!!

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