K-Means (Kernel)


Synopsis

Clustering with kernel k-means


Description

This operator is an implementation of kernel k means. Kernel K Means uses kernels to estimate distance between objects and clusters. Because of the nature of kernels it is necessary to sum over all elements of a cluster to calculate one distance. So this algorithm is quadratic in number of examples and returns NO CentroidClusterModel, as its older brother KMeans does. This operator will create a cluster attribute if not present yet.


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ExampleProcess