Barclays Interview Questions | K mean

Question

How can we make sure that K-Means output is not sensitive to initialization?

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Dhruv2301 55 years 1 Answer 769 views Great Grand Master 0

Answer ( 1 )

  1. K-Means is a relatively efficient method.

    However, specifying the number of clusters, in advance therfore the final results are sensitive to initialization but it often terminates at a local optimum.

    I haven’t come across any other method to make it less sensitive during my career. Other people can please add

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