This package provides functions that manipulate data in kernel space, such as centerization in kernel space, computing distance from kernel, etc.
Many kernel algorithms for machine learning are provided including kernel PCA, kernel regression, kernel kmeans, etc. Also the corresponding linear version of these algorithms are also provided to show that kernel methods with linear kernel is equivalent to linear version methods. Please try the demo script in the package.
This package is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).