What is the difference between k-means clustering and minimum-variance quantization?

  • Thread starter czechman45
  • Start date
  • #1
12
0
Hi,

I have a situation where I have a set of n data points and want to specify k values that best approximate the values in the set. (it's an image-color reduction problem)

MATLAB has a magic algorithm using something called minimum-variance quantization that will do this (although I can't find a description of how this actually works). I've also stumbled upon something called k-means clustering. What is the difference between these two or are they the same? Where might I be able to learn about these? I found some information describing k-means clustering, but I couldn't find anything on minimum-variance quantization.

Thank you!
 

Answers and Replies

Related Threads on What is the difference between k-means clustering and minimum-variance quantization?

Replies
4
Views
2K
Replies
1
Views
8K
Replies
2
Views
3K
Replies
6
Views
20K
Replies
2
Views
1K
Replies
2
Views
85K
Replies
6
Views
2K
Replies
2
Views
2K
Top