Fast Implementations of Kernel K-Means
Classify new data based on kkmeans result
Get the kernel matrix for a dataset
Get the average distance to each points k-nearest neighbor
Function to get jump statistic for varying values of k
An Efficient Kernel K-Means Algorithm
Estimate the bandwidth parameter for a gaussian kernel using MATr
Implementations several algorithms for kernel k-means. The default 'OTQT' algorithm is a fast alternative to standard implementations of kernel k-means, particularly in cases with many clusters. For a small number of clusters, the implemented 'MacQueen' method typically performs the fastest. For more details and performance evaluations, see Berlinski and Maitra (2025) <doi:10.1002/sam.70032>.