'what is convergence in k Means?

I have a very small question related to unsupervised learning because my teacher have not use this word in any lectures. I got this word while reading tutorials. Does this mean if values are same to initial values in last iteration of clusters then it is called converge? for example

      |  c1   |  c2  | cluster
      | (1,0) | (2,1)|
      |-------|------|------------
A(1,0)| ..    |..    |get smallest value
B(0,1)|..     |...   |
c(2,1)|..     |...   |
D(2,1)|..     |....  |

now after performing n-iteration and if values come same in both c1 and c2 that is (1,0) and (2,1) in last n-th iteration and taking avg if other than single , is it convergence?

artificial-intelligence unsupervised-learning

Solution 1:^[1]

Incase of K-means clustering, the word convergence means the algorithm have successfully completed this clustering or grouping of data points in k number of clusters.The algorithm will make sure it has completely grouped the data points into correct clusters, if the centroids (k values) in k-means remains same place or in point for 2 iteration .

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Solution 1	shilash M

'what is convergence in k Means?

Solution 1:[1]

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Solution 1:^[1]