Table 2.
DT | UC | PC | DCB | KNN | ||||
---|---|---|---|---|---|---|---|---|
γ = 0.1 | γ = 1 | γ = 10 | K = 1 | K = 5 | K = 10 | |||
0.7653 | 0.6642 | 0.7914 | 0.4114 | 0.8075 | 0.8278 | 0.7447 | 0.7147 | 0.6872 |
Here DT means decision tree algorithm, UC means the usual correlation kernel, PC stands for the parsimonious correlation we proposed, DCB is the novel kernel proposed by us representing denoised correlation-based kernel, and KNN is the K-nearest neighborhood algorithm.