How to do K-Means clustering on data that goes beyond 3 dimensions?

2 次查看(过去 30 天)
I have done K-means clustering before but always on datasets that could be plotted in a 2D or 3D space. Right now I have a 35*6 matrix and need to make clusters based on those 6 dimensions. How can I program these clusters and still be able to retrieve the data to know which data point is in which group? Since I don't have any idea how to cluster past these 3 dimensions I don't have written any script yet, that's why I am only looking for some guidance and direction to understand how to do it and begin writing.
Thanks in advance, I really appreciate the help!
  2 个评论
Kelly Kearney
Kelly Kearney 2021-10-23
The process is exactly the same as for 2 or 3 dimensions:
idx = kmeans(rand(35,6), 6);
Visualizing the results may be more complicated...
Pietro Quinzani
Pietro Quinzani 2021-10-23
编辑:Pietro Quinzani 2021-10-23
@Kelly Kearney Oh cool, so it's easier than I thought. I don't really need to visualize it though but how can I track through idx in which group is each data point?

请先登录,再进行评论。

回答(0 个)

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by