question about determining the correct number of clusters (documentation)
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I have a question about determining the correct number of clusters (in k-means clustering).
In the documentation, there is a section about 'determining the correct number of clusters'. Please help me understand what the arguments in the table are for: iter (which would mean iterations), phase (?), num (?), and sum(?).
In the example, you will see:
Best total sum of distances = 1771.1
Here are my questions:
- Are we going for the best total sum of distances?
- From here, how are we able to determine that 4 is indeed the correct?
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回答 (1 件)
Bernhard Suhm
2018 年 10 月 3 日
You can use the silhouette plot or evalclusters function to evaluate the quality of your clustering. There's a little more info in this previous answer.
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