MATLAB: When we applied k-means cluster on FM, where FM is Feature Matrix with k=2 it gives us 2 cluster, again we want to apply k-means for the obtained clusters individually until clusters becomes single value. How to apply k-means cluster recursively.

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Use a while loop.

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MATLAB: K-means clustering

Since k-means uses a random start, the clusters have no particular order they come out in. Therefore, you need to identify which cluster is a hand.

Surely there are features about a hand that make it different from the background? Color perhaps, or shape. You need to start thinking about what makes a hand a hand.

MATLAB: K-means Clustering

kmeans chooses seeds by a random process if you do not specify initial locations using the 'start' option. Information on how the algorithm works is in the 'More about' section of the documentation

doc kmeans

There is no way for the algorithm to know what you call 'object' and what you call 'background'. If you give it two start seeds, one in the object and one in the background then these will always remain in this order, but otherwise they can change around with each run of the algorithm unless you fix the random seed, but that would only keep the class centres the same for the same data, not across different data sets obviously.

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MATLAB: K-means clustering

MATLAB: K-means Clustering

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