Fig. 1From: Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional dataComparison of test correlation averaged over simulation runs in Data 1. The horizontal axis denotes the number of dimensions D, and the vertical axis denotes test correlations. The number of training samples is 50, 100, and 150. TSKCCA outperforms SAFCCA, especially with high-dimensional dataBack to article page