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Is it possible to get same results in K-means clustering for multiple runs?
K-Means clustering algorithm instead converses on local minima which might also correspond to the global minima in some cases but not always. However, note that it’s possible to receive same clustering results from K-means by setting the same seed value for each run.
What does multiple K mean?
The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately.
Does k-means always give same result?
They won’t necessarily be the same. Consider observations equally distributed over a circle (radius = 1). Depending on the initial centroids, the algorithm will converge on different solutions.
How to mitigate the dependence of k-means?
For a low k, you can mitigate this dependence by running k-means several times with different initial values and picking the best result. As k increases, you need advanced versions of k-means to pick better values of the initial centroids (called k-means seeding ).
What are the advantages and disadvantages of k-means?
Clustering data of varying sizes and density. k-means has trouble clustering data where clusters are of varying sizes and density. To cluster such data, you need to generalize k-means as described in the Advantages section.
Why do we need advanced versions of k-means?
As k increases, you need advanced versions of k-means to pick better values of the initial centroids (called k-means seeding ). For a full discussion of k- means seeding see, A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm by M. Emre Celebi, Hassan A. Kingravi, Patricio A. Vela.
What does a minus sign in k-means mean?
Here a minus sign (−) represents a centroid that is not needed, and a plus sign (+) a cluster where more centroids would be needed. K-means cannot do it because there are stable clusters in between.