Fig. 3From: Stratifying patients using fast multiple kernel learning framework: case studies of Alzheimer’s disease and cancersThe illustration of Multiple Kernel Learning given that \( {\mathcal{X}}_i \) is original dataset, Ki is kernel matrix that is constructed by kernel function ki, βi is weighted coefficient combining K1 to KM to unify a final kernel matrix K, \( {\mathcal{H}}_i \) is the Hilbert space of ith dataset in the kernel methodBack to article page