Mathematical Problems in Engineering / 2020 / Article / Tab 1

Research Article

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.

PCASPCAFP-SPCA
PC1PC2PC3PC1PC2PC1PC2

0.37080.1993−0.26980.500.50
0.37080.1993−0.26980.500.50
0.37080.1993−0.26980.500.50
0.37080.1993−0.26980.500.50
0.2625−0.42280.04830−0.50−0.5
0.2625−0.42280.04830−0.50−0.5
0.2625−0.42280.04830−0.50−0.5
0.2625−0.42280.04830−0.50−0.5
0.29540.25100.59140000
0.29540.25100.59140000
(%)58.9933.107.9132.4929.8640.0036.76

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.