In this script a soft-k-means algorithm is implemented and its effectiveness is shown by running through an example. First, 100 samples from a Gaussian mixture distribution are drawn. Subsequently, the update and assignment steps are performed 10 times. The found cluster centers are quite accurate which can be seen in the figure or by comparing the numeric results to the Gaussian distribution centers.
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An implementation of the soft-k-means algorithm in Matlab
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- MATLAB 100.0%