Detailed Description

Kernel centroid cluster representation.

Author: E.Noirfalise

Date: 2018/08/06

Copyright: 2018 Reactiv'IP, all right reserved.

The approach is based on a projection of the feature vectors to a low dimensional subspace spanned by a small subset of these samples. It represents a weighted sum of sample points in a kernel induced feature space

See also: The Kernel Recursive Least Squares Algorithm, Yaakov Engel, Shie Mannor, Ron Meir, 2003

Note: this code is inspired of dlib implementation of Kernelized KMeans algorithm (see http://dlib.net/)

The documentation for this class was generated from the following file:

/media/reactivipdev/Nightly/IPSDK_Patch/IPSDK_4_1/IPSDK_Nightly/include/public/IPSDKMath/Clustering/KernelKMeansCentroid.h