Definitions from Wikipedia (Kernel embedding of distributions)

▸ noun:  In machine learning, the kernel embedding of distributions (also called the kernel mean or mean map) comprises a class of nonparametric methods in which a probability distribution is represented as an element of a reproducing kernel Hilbert space .A.


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