Sparse Principal Component Analysis via Fractional Function Regularity
Table 1
Loadings and variance of numerical results of PCA, SPCA, and FP-SPCA methods in Case 1, where the SPCA and FP-SPCA methods have the same performance in obtaining the sparse loadings while FP-SPCA performs better than SPCA in adjusted variance. (%) denotes the adjusted variance.