When using the linear kernel or cosine similarity, the estimator of PHSIC in feature space (14) is as follows: Generally in kernel methods, a feature map φ(•) induced by a kernel k(•, •) is unknown or highdimensional and it is difficult to compute estimated values in feature space 6 .
when we use the linear kernel or cosine similarity, feature maps can be explicitly determined (Equation 19).